{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "55e2351f-fc09-4446-9ea2-04d121fa72ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import statsmodels.formula.api as smf\n",
    "import statsmodels.api as sm\n",
    "from statsmodels.formula.api import ols\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.stats import linregress\n",
    "from datetime import date\n",
    "complete_nov = date(2022,10,27)\n",
    "intervention_date = pd.to_datetime('2022-10-27')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e256b2bf-24b9-4c9c-a677-33695b8ad192",
   "metadata": {},
   "source": [
    "# Timeseries with Confidence Interval Figure 1 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "65c55d38-8f31-4c71-a72a-4cc05629b14d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "daily_values_panel = pd.read_csv('daily_info_quality_panel.csv')\n",
    "daily_values_deca = pd.read_csv('daily_info_quality_decahose.csv')\n",
    "info_qual_panel = pd.read_csv('monthly_info_quality_panel.csv')\n",
    "info_qual_decahose = pd.read_csv('monthly_info_quality_decahose.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0558b405-97ce-466c-bc99-cb8f81764a6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "bef_panel = info_qual_panel[info_qual_panel.month_year<'2022-11-01']\n",
    "aft_panel = info_qual_panel[info_qual_panel.month_year>='2022-11-01']\n",
    "bef_deca = info_qual_decahose[info_qual_decahose.month_year<'2022-11-01']\n",
    "aft_deca = info_qual_decahose[info_qual_decahose.month_year>='2022-11-01']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e05f0aea-8ee6-4992-9f78-3e8cdc1dcd3b",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "# Function to perform bootstrapping and calculate trend values and CIs\n",
    "def calculate_trend_values_with_ci(dataframe, num_iterations=1000):\n",
    "    # Initialize an empty list to store trend values for each row across all iterations\n",
    "    \n",
    "    dataframe['date'] = pd.to_datetime(dataframe['date'])\n",
    "    dataframe['month_year'] = dataframe['date'].dt.to_period('M')\n",
    "    dataframe['month_year'] = dataframe['month_year'].dt.to_timestamp()\n",
    "\n",
    "    # Initialize list to store the bootstrapped trend values for each time point\n",
    "    all_trend_values = [[] for _ in range(len(dataframe['month_year'].unique()))]\n",
    "\n",
    "    # Bootstrapping approach over num_iterations iterations\n",
    "    for i in range(num_iterations):\n",
    "        # Resample the data with replacement\n",
    "        resampled_data = dataframe.sample(frac=1, replace=True)\n",
    "        \n",
    "        # Calculate the monthly averages for each resampled dataset\n",
    "        monthly_avgs = resampled_data.groupby('month_year', as_index=False)['info_qual'].mean()\n",
    "\n",
    "        # Check if all x values (month_year) are identical, skip if true\n",
    "        if monthly_avgs.month_year.nunique() == 1:\n",
    "            continue\n",
    "\n",
    "        # Add 'time' column as numeric time representation for regression\n",
    "        monthly_avgs['time'] = (monthly_avgs['month_year'] - monthly_avgs['month_year'].min()).dt.days\n",
    "\n",
    "        # Perform OLS regression with Newey-West standard errors\n",
    "        model = smf.ols('info_qual ~ time', data=monthly_avgs).fit(cov_type='HAC', cov_kwds={'maxlags': 1})\n",
    "\n",
    "        # Get regression coefficients (intercept and slope)\n",
    "        intercept = model.params['Intercept']\n",
    "        slope = model.params['time']\n",
    "\n",
    "        # Calculate trend values for the original time points\n",
    "        trend_values = intercept + slope * monthly_avgs['time']\n",
    "\n",
    "        # Append the trend values for each iteration to the corresponding month\n",
    "        for idx, trend in enumerate(trend_values):\n",
    "            all_trend_values[idx].append(trend)\n",
    "\n",
    "    # Store the bootstrapped trend values in the DataFrame\n",
    "    monthly_avgs['trend_values'] = all_trend_values\n",
    "\n",
    "    # Calculate the mean trend and 95% confidence intervals (2.5th and 97.5th percentiles)\n",
    "    monthly_avgs['mean_trend'] = monthly_avgs['trend_values'].apply(np.mean)\n",
    "    monthly_avgs['lower_ci'] = monthly_avgs['trend_values'].apply(lambda x: np.percentile(x, 2.5))\n",
    "    monthly_avgs['upper_ci'] = monthly_avgs['trend_values'].apply(lambda x: np.percentile(x, 97.5))\n",
    "\n",
    "    return monthly_avgs\n",
    "\n",
    "# Example usage:\n",
    "# Assuming bef_panel, aft_panel, bef_deca, and aft_deca are already loaded and processed DataFrames\n",
    "bef_panel = daily_values_panel[daily_values_panel.date<'2022-11-01'].reset_index(drop=True)\n",
    "aft_panel = daily_values_panel[daily_values_panel.date>='2022-11-01'].reset_index(drop=True)\n",
    "bef_deca = daily_values_deca[daily_values_deca.date<'2022-11-01'].reset_index(drop=True)\n",
    "aft_deca = daily_values_deca[daily_values_deca.date>='2022-11-01'].reset_index(drop=True)\n",
    "\n",
    "# Apply the bootstrapping function to each dataset\n",
    "bef_deca = calculate_trend_values_with_ci(bef_deca, num_iterations=1000)\n",
    "aft_deca = calculate_trend_values_with_ci(aft_deca, num_iterations=1000)\n",
    "bef_panel = calculate_trend_values_with_ci(bef_panel, num_iterations=1000)\n",
    "aft_panel = calculate_trend_values_with_ci(aft_panel, num_iterations=1000)\n",
    "\n",
    "# The resulting DataFrame `bef_deca` will now contain:\n",
    "# - 'mean_trend': The mean trend values calculated from bootstrapped samples\n",
    "# - 'lower_ci': The 2.5th percentile of the bootstrapped trend values (lower bound of the 95% CI)\n",
    "# - 'upper_ci': The 97.5th percentile of the bootstrapped trend values (upper bound of the 95% CI)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4c6215c2-f7f4-4ee4-84c9-b2af14c81781",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function matplotlib.pyplot.show(close=None, block=None)>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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jVc2FEDYzcOBAq+n69etz/vz5p663fv16AgIC6Natm2Wek5MTQ4cORa/Xs2PHDqvlX331VUuJyuP69u1rea3VaqlZsyaKotCnTx/LfB8fH8qVK2cVm1artbQBNJvN3Lt3D6PRSM2aNfnzzz+fegzpHReoVX0flVJa9Ntvv1nNr1ixoqUUGNRSo8fjTEtsbCwAnp6e6S6T8l7Kspmh0+ksrxMTE7lz5w4vvvgiQJbPTVp69uzJ/v37iYyMtMxbvnw5JUqUoGHDhhnaxqOl5RqNhsGDB5OcnMzmzZsBCAsLo3bt2ixfvtyy3L1799iwYQPdu3fP8eHgHv18pnwO3d3d6dy5s2V+uXLl8PHxsbruK1asoH79+hQqVIg7d+5Y/po2bYrJZGLnzp3p7tPPz4/y5ctbltmzZw9arZYRI0Zw69Ytzp49C6gl3vXq1cvWOejSpQuFChWyTKd8njNyHwC1WcGjpcVvvfUWjo6Olu/Spk2biI6Oplu3blbnQavVUrt2bavq0Wk5dOgQUVFRDBo0yKoGRevWrSlfvnyq72RKDI9asWIF3t7eNGvWzCqG559/Hg8Pj6fGkNnvU1r31bt37xITEwP8e59JqbmQIqNDfeXEvQ9g1apVmM1mOnfubHWeAgICKFu2bKrz5OLiQu/evbO8v0c9/n/EvXv32Lp1K507dyY2NtYSy927d2nRogVnz55N1dSgf//+Vt+F+vXrYzKZuHTpEgCbN28mOTnZ0mwjRXaHWHvadygzx+Lj48OJEycs33EhhH1JVXMhhE24urqmSoYLFSqUoTaPly5domzZsql63K5QoYLl/UelVL9NS8mSJa2mvb29cXV1tVSBfHT+420qlyxZwtSpUzl16hQGgyFD+3uSS5cu4eDgYNUbNkBAQAA+Pj6pjuvx2CFj5/DRpDq9jqRSEm5/f/+Mhm9x7949xowZww8//GDpsCrFgwcPMr299HTp0oV3332X5cuXM3LkSB48eMC6desYNmxYhpJBBwcHSpcubTUvLCwMwKrNac+ePRk8eDCXLl0iODiYFStWYDAYcnxou7S+I97e3hQvXjzV8Xl7e1td97Nnz3L8+PF0Hzg9fl0eV79+fUuCtmvXLmrWrEnNmjUpXLgwu3btomjRohw7dozXX389K4dm8fhnOCWByMh9AKBs2bJW0x4eHgQGBlquX0oC0bhx4zTX9/LyeuL2U75z5cqVS/Ve+fLl2b17t9U8R0dHihcvbjXv7NmzPHjwIN3v0tOuRWa/T086p15eXpb7TEpV+hRpHWN6bH3vA/U8KYqS6pqmeLw6frFixWzWAdrjcZ87dw5FUfj000/59NNP01wnKiqKYsWKWaaf9llO+Sw9fnx+fn5WiXNmPW2/mTmWsWPH0q5dO8LCwnjuuedo2bIlb7zxxhObRwkhco4k3kIIm9Bqtbm2r0dLjDISR3qxKY90NrVs2TIiIiJo3749I0aMwN/fH61Wy4QJE6xKYLMioyWIGYkzLRUrVmTNmjUcP3483fa5x48fB7AkpunFlNIZ3qM6d+7M3r17GTFiBNWqVcPDwwOz2UzLli1tOhxOoUKFaNOmjSXxXrlyJUlJSTZvd921a1eGDRvG8uXL+eijj1i2bBk1a9bMVKKSFeld34xcd7PZTLNmzfjPf/6T5rIpDxjSU69ePb7++mvOnz/Prl27qF+/PhqNhnr16rFr1y6CgoIwm81WNS6yIquf4YxK+bwtXbqUgICAVO/belQBFxeXVA8EzWYz/v7+VrUmHpXew5EUmf0+5fQ5zal7n9lsRqPRsGHDhjSPwcPDw2r6Sff1zHp8Wynndfjw4bRo0SLNdR5/QJrT5z09T9tvZo6lQYMGREZGsnbtWn7//XcWLFjA9OnTmTt3rlXtGyFE7pDEWwhhd8HBwRw/fhyz2Wz1I/fUqVOW93PaypUrKV26NKtWrbJKSh8fbzwz1XCDg4Mxm82cPXvWUnoPau/R0dHRNjuutm3b8vnnn/Ptt9+mmXibTCa+++47ihYtank/pRQlOjraatnHS+Hv37/Pli1bGDNmDCNHjrTMz2rVxaedv549e9KuXTsOHjzI8uXLqV69+hM7lnuU2Wzm/PnzVknomTNnAKx6Dy5cuDCtW7dm+fLldO/enT179jyxc7K8IDQ0FL1en+XxqFMS6k2bNnHw4EHLePMNGjRgzpw5BAUF4e7uzvPPP//E7eR0VfyzZ8/SqFEjy7Rer+fGjRu0atUKwFKq6+/vn6VzkfKdO336dKpS89OnT2foOxkaGsrmzZupW7duppNFW3+f4N/7TGRkpNXDo9OnT2do/Yze+9KT3mciNDQURVEoVarUUx8MZVZmP4cpDxydnJxsNqZ7ymfl7NmzVjVtbt++neEaHlmR2WMpXLgwvXv3pnfv3uj1eho0aMDo0aMl8RbCDqSNtxDC7lq1asXNmzeteos1Go3MnDkTDw+PDLfvzY6UUoZHSzP279/Pvn37rJZL6dX48YQ1LSnJwuNJ3bRp0wAy3Ovw07z44os0b96cRYsWsW7dulTvf/zxx5w5c4b//Oc/lhLB4OBgtFptqrbBs2fPtppO67xA6mPKqJQxkNM7fy+//DJFihRh0qRJ7NixI9Ol3bNmzbK8VhSFWbNm4eTklKon9zfeeIN//vmHESNGoNVq6dq1a+YOJJd17tyZffv28b///S/Ve9HR0RiNxieuX6pUKYoVK8b06dMxGAzUrVsXUBPyyMhIVq5cyYsvvvjUEuOnXb/smj9/vlVV5zlz5mA0Gnn55ZcBaNGiBV5eXnz++edWy6VIazi6R9WsWRN/f3/mzp1rNaTfhg0bOHnyZIa+k507d8ZkMjFu3LhU7xmNxieeG1t/nwDLuXl0aLjMbDOj9770pPeZ6NixI1qtljFjxqQ6XkVRMjQcYWb3mR5/f3/Cw8OZN28eN27cSPX+0z43aWnatClOTk7MnDnT6vhy+iFeZo7l8XPs4eFBmTJlUg1nKYTIHVLiLYSwu/79+zNv3jwiIiI4fPgwISEhrFy50lIS+aROw2ylTZs2rFq1ig4dOtC6dWsuXLjA3LlzqVixInq93rKcTqejYsWK/Pjjj4SFhVG4cGGee+45yzBNj6patSq9evVi/vz5REdH07BhQw4cOMCSJUto3769Vcledn377bc0btyYdu3a8frrr1O/fn2SkpJYtWoV27dvp0ePHgwbNsyyvLe3N6+99hozZ85Eo9EQGhrKunXrUrU59fLysgx/ZTAYKFasGL///jsXLlzIUpyhoaH4+Pgwd+5cPD09cXd3p3bt2pY2mU5OTnTt2pVZs2ah1WqtOtx7GldXVzZu3EivXr2oXbs2GzZs4LfffuOjjz5KVf23devW+Pr6smLFCl5++eUstX3PTSNGjOCXX36hTZs2liHm4uLi+Ouvv1i5ciUXL15M1Y/B4+rXr88PP/xA5cqVLTUeatSogbu7O2fOnMlQ++6UEvGhQ4fSokULmz+0SE5OpkmTJnTu3JnTp08ze/Zs6tWrZxmf3svLizlz5vDGG29Qo0YNunbtip+fH5cvX+a3336jbt26Vg9fHufk5MSkSZPo3bs3DRs2pFu3bpbhxEJCQqy+I+lp2LAhAwYMYMKECRw9epTmzZvj5OTE2bNnWbFiBf/973/p1KlTmuva+vsEUK1aNbp168bs2bN58OABderUYcuWLZw7dy5D62f03peelM/Exx9/TNeuXXFycqJt27aEhoby2Wef8eGHH3Lx4kXat2+Pp6cnFy5cYPXq1fTv35/hw4dn6Ziz8jn86quvqFevHpUrV6Zfv36ULl2aW7dusW/fPq5evcqxY8cyFYOfnx/Dhw9nwoQJtGnThlatWnHkyBE2bNjw1O9idmX0WCpWrEh4eDjPP/88hQsX5tChQ6xcudKqE0ohRO6RxFsIYXc6nY7t27fzwQcfsGTJEmJiYihXrhyLFi0iIiIiV2KIiIjg5s2bzJs3j//9739UrFiRZcuWsWLFCrZv32617IIFCxgyZAjDhg0jOTmZUaNGpZl4pyxbunRpFi9ezOrVqwkICODDDz/McDXOjCpatCj79+9n2rRp/PTTT6xcuZLExEQAPv30U8aOHZtqnZkzZ2IwGJg7dy4uLi507tyZyZMnpzqW7777jiFDhvDVV1+hKArNmzdnw4YNBAUFZTpOJycnlixZwocffsjAgQMxGo0sWrTIqjOknj17MmvWLJo0aUJgYGCGt63Vatm4cSNvvfUWI0aMwNPTk1GjRllV6U3h7OxMly5dmD17do53qmYLbm5u7Nixg88//5wVK1bw7bff4uXlRVhYGGPGjMHb2/up20hJvOvVq2eZ5+joyEsvvcTmzZsz1L67Y8eODBkyhB9++IFly5ahKIpNE+9Zs2ZZ2vgbDAa6devGl19+aVW1+PXXXycoKIiJEycyefJkkpKSKFasGPXr189Qr9gRERG4ubkxceJE/u///g93d3c6dOjApEmT0u2c8HFz587l+eefZ968eXz00Uc4OjoSEhJCjx49LLUJ0mPL71OKb775Bj8/P5YvX86aNWto3Lgxv/32GyVKlHjqupm596WlVq1ajBs3jrlz57Jx40bMZjMXLlzA3d2dDz74gLCwMKZPn86YMWMAKFGiBM2bN7c8TMmKrHwOK1asyKFDhxgzZgyLFy/m7t27+Pv7U7169TTvERnx2Wef4erqyty5c9m2bRu1a9fm999/t1ltpvRk9FiGDh3KL7/8wu+//05SUhLBwcF89tlnjBgxIkfjE0KkTaPkdC8RQggh7OLatWvUqVMHo9HIvn370uw1PS86duwY1apV49tvv83RpHjYsGEsXLiQmzdvWpoQCCGEEELkBGnjLYQQBVSxYsXYuHEjiYmJvPzyyzna4Y8tff3113h4eNCxY8cc20diYiLLli3j1VdflaRbCCGEEDlOqpoLIUQBVqFChWx1YpSbfv31V/755x/mz5/P4MGDLR0o2VJUVBSbN29m5cqV3L17l3feecfm+xBCCCGEeJxUNRdCCJEnhISEcOvWLVq0aMHSpUtzpFO97du306hRI/z9/fn000+lkyEhhBBC5ApJvIUQQgghhBBCiBwkbbyFEEIIIYQQQogcJIm3EEIIIYQQQgiRgwp852pms5nr16/j6elpNQ6oEEIIIYQQQgiRVYqiEBsbS1BQEA4OTy7TLvCJ9/Xr1ylRooS9wxBCCCGEEEIIUQBduXKF4sWLP3GZAp94p/SKe+XKFby8vOwcTfoMBgO///47zZs3x8nJyd7hiAyQa5a/yfXL/+QaFgxyHfM/uYb5m1y//EeuWd4RExNDiRIlMjQSS4FPvFOql3t5eeX5xNvNzQ0vLy/5AuUTcs3yN7l++Z9cw4JBrmPeFB8fT61atQA4ePAgbm5u6S4r1zB/k+uX/8g1y3sy0qS5wCfeQgghhBAicxRF4Z9//rG8FkIIkT2SeAshhBBCCCuurq5s27bN8loIIUT2SOIthBBCCCGsaLVawsPD7R2GEEIUGJJ4CyGEEEKIAsNkMmEwGOwdRr5hMBhwdHQkMTERk8lk73BEBsg1yz1OTk5otVqbbEsSbyGEEEIIYcVoNLJu3ToA2rRpg6Nj3v/JqCgKN2/eJDo62t6h5CuKohAQEMCVK1cy1EGUsD+5ZrnLx8eHgICAbJ/rvH8XFUIIIYQQuSopKYkOHToAoNfr80XinZJ0+/v74+bmJglJBpnNZvR6PR4eHjg4ONg7HJEBcs1yh6IoxMfHExUVBUBgYGC2tpf376JCCCGEECJXOTg4UKdOHcvrvM5kMlmSbl9fX3uHk6+YzWaSk5NxdXXNF9dayDXLTTqdDoCoqCj8/f2zVe1cEm8hhBBCCGFFp9OxZ88ee4eRYSltup803rgQQmRFyn3FYDBkK/GWRyRCCCGEEKJAkOrlQghbs9V9RRJvIYQQQgghhBAiB0niLYQQQgghrCQkJFCrVi1q1apFQkKCvcMROejixYsUKlSIo0eP2juUp4qIiKB9+/aW6fDwcN59913LdEhICDNmzMj1uLIqI/GOHj2aatWq5Uo8ImdJ4i2EEEIIIayYzWYOHTrEoUOHMJvN9g6nwIqIiECj0aDRaHB2dqZMmTKMHTsWo9Fo79AANSlPiS+9v8WLF9s7TIuDBw/Sv39/e4eRYY/Hq9FoWLNmjU22/dNPP1GtWjXc3NwIDg5m8uTJVu9v3749zet58+ZNyzLLly+nRIkSFCpUiPfee89q/YsXLxIWFkZMTEyG4vn5558JDw/H29sbDw8PqlSpwtixY7l37x4AixcvxsfHJ3sHncdJ52pCCCGEEMKKi4uLZRxvFxcXO0dTsLVs2ZJFixaRlJTE+vXrefvtt3FycuLDDz+0d2iUKFGCGzduWKanTJnCxo0b2bx5s2Wet7e35bXJZEKj0ditp20/Pz+77DercireDRs20L17d2bOnEnz5s05efIk/fr1Q6fTMXjwYKtlT58+jZeXl2Xa398fgDt37tC3b18WL15M6dKlad26NY0bN6ZNmzYADBo0iIkTJ1qtm56PP/6YSZMmMWzYMD7//HOCgoI4e/Ysc+fOZenSpbzzzjs2PPq8S0q8hRBCCCFyQEJCArdu3cqXVbUdHR1p3bo1rVu3zhdjeOdnLi4uBAQEEBwczFtvvUXTpk355ZdfAJg2bRqVK1fG3d2dEiVKMGjQIPR6vWXdlFLC//3vf1SoUAEPDw9atmxplSwDLFiwgAoVKuDq6kr58uWZPXt2hmLTarUEBARY/jw8PHB0dLRMb9y4kcDAQH755RcqVqyIi4sLly9fJikpieHDh1OsWDHc3d2pXbs227dvz1TcJpOJ9957Dx8fH3x9ffnPf/6DoihPjPfxqtsajYYFCxbQoUMH3NzcKFu2rOXcpvj77795+eWX8fDwoGjRorzxxhvcuXPH8v7KlSupXLkyOp0OX19fmjZtSlxcXJr7r1mzJlOmTLFMt2/fHicnJ8s1u3r1KhqNhnPnzqWKNyQkBIAOHTqg0Wgs0ymWLl1KSEgI3t7edOvWjdjY2HTPw9KlS2nfvj0DBw60JM0ffvghkyZNSnUO/f39ra5xykOT8+fP4+3tTZcuXahVqxaNGjXi5MmTAHz//fc4OTnRsWPHdGNIceDAAT7//HOmTp3K5MmTqVOnDiEhITRr1oyff/6ZXr16PXUbBYUk3kIIIYQQNrR79246vdoRT08PAgIC8PT0oNOrHfPV8Fz5nqKAMc4+f09JDp9Gp9ORnJwMqGOof/nll5w4cYIlS5awdetW/vOf/1gtHx8fz5QpU1i6dCk7d+7k8uXLDB8+3PL+8uXLGTlyJOPHj+fkyZN8/vnnfPrppyxZsiRbcT66/0mTJrFgwQJOnDiBv78/gwcPZt++ffzwww8cP36c1157jZYtW3L27NkMxz116lQWL17MN998w+7du7l37x6rV6/OdHxjxoyhc+fOHD9+nFatWtG9e3dL9ebo6GgaN25M9erVOXToEBs3buTWrVt07twZgBs3btCtWzfefPNNTp48yfbt2+nYsWO6DwAaNmxoecCgKAq7du3Cx8eH3bt3A7Bjxw6KFStGmTJlUq178OBBABYtWsSNGzcs0wCRkZGsWbOGdevWsW7dOnbu3PnEtuFJSUm4urpazdPpdFy9epVLly5Zza9WrRqBgYE0a9bM6h5VtmxZ4uPjOXLkCPfu3ePgwYNUqVKF+/fv8+mnnzJr1qx09/+o5cuX4+HhwaBBg9J8v6BXL3+UPMIUQgghhLCROXPm8Pbbb1OhuJYp3cyEFoXIW2a+3vEr9euvYfbs2QwcONDeYT6VyWRi69atADRu3DhbY9fahSkefvKwz74768HRPdOrKYrCli1b+N///seQIUMAUnUc9tlnnzFw4ECrEmuDwcDcuXMJDQ0FYPDgwYwdO9by/qhRo5g6daqldLJUqVL8888/zJs3zyaljQaDgdmzZ1O1alUALl++zKJFi7h8+TJBQUEADB8+nI0bN7Jo0SI+//zzDMU9Y8YMPvzwQ0vcc+fO5X//+1+m44uIiKBbt24AfP7553z55ZccOHCAli1bMmvWLKpXr26JCeCbb76hRIkSnDlzBr1ej9FopGPHjgQHBwNQuXLldPcVHh7OwoULMZlM/P333zg7O9OlSxe2b99Oy5Yt2b59Ow0bNkxz3ZRq5z4+PgQEBFi9ZzabWbx4MZ6engD06NHDqgbB41q0aMGwYcOIiIigUaNGnDt3jqlTpwLqw4SQkBACAwOZO3cuNWvWJCkpiQULFhAeHs7+/fupUaMGhQoVYsmSJfTs2ZOEhAR69uxJixYt6NOnD4MHD+bChQu88sorGAwGRo8eTadOndKM5ezZs5QuXRonJ6d0431WSOIthBBCCGEDu3fv5u2332ZIc4XpPYw82sx1aAsj7y5V20VWrlyZunXr2i/QDEhMTKR58+YA6PV63N0zn0iKjFm3bh0eHh4YDAbMZjOvv/46o0ePBmDz5s1MmDCBU6dOERMTg9FoJDExkfj4eNzc3ABwc3OzJK8AgYGBREVFARAXF0dkZCR9+vShX79+lmWMRqNV2+zscHZ2pkqVKpbpv/76C5PJRFhYmNVySUlJ+Pr6WqafFPeDBw+4ceMGtWvXtrzv6OhIzZo1n1rd/HGPxubu7o6Xl5dlP8eOHWPbtm14eKR+SBMZGUnz5s1p0qQJlStXpkWLFjRv3pxOnTpRqFChNPdVv359YmNjOXLkCHv37qVhw4aEh4czceJEQC3xHjFiRKbiB/WhS0rSDeq5un37drrL9+vXj8jISNq0aYPBYMDLy4t33nmH0aNHW6qSlytXjnLlylnWqVOnDpGRkUyfPp2lS5cCarX3Dh06WJbZsWMHx48fZ+bMmZQpU4bvv/+egIAAXnjhBRo0aGBpH/6ozF6vgkwSbyGEEEIIG5gxfRoVimtTJd0ADg4w4w3YclLLjOnT83zi7eDgYCnBtFdHWdmidVNLnu2170xo1KgRc+bMwdnZmaCgIEub+osXL9KmTRveeustxo8fT+HChdm9ezd9+vQhOTnZkng/XpKo0WgsyU5K2+Kvv/7aKokFbFaLQafTodFoLNN6vR6tVsvhw4dT7ePRBPdJcdtSWvtJ6alfr9fTtm1bJk2alGq9wMBAtFotmzZtYu/evfz+++/MnDmTjz/+mP3791OqVKlU6/j4+FC1alW2b9/Ovn37aNasGQ0aNKBLly6cOXOGs2fPplvindVjSItGo2HSpEl8/vnn3Lx5Ez8/P7Zs2QJA6dKl013vhRdesFSLf1xSUhKDBg1i6dKlnDt3DqPRaDmWsLAw9u/fT9u2bVOtFxYWxu7duzEYDM98qXc+vJMKIYQQQuQtCQkJrFm7ln4NUyfdKRwcoF9DI6vXrM7zHa7pdDqOHj3K0aNH0el09g4n8zQatbq3Pf4eSUIzwt3dnTJlylCyZEmrjuwOHz6M2Wxm6tSpvPjii4SFhXH9+vVMbbto0aIEBQVx/vx5ypQpY/WXVuJoC9WrV8dkMhEVFZVqn49XoU6Pt7c3gYGB7N+/3zLPaDRy+PBhm8Zao0YNTpw4QUhISKpYU2p5aDQa6taty5gxYzhy5AjOzs5PbGvesGFDtm3bxs6dOwkPD6dw4cJUqFCB8ePHExgYmKomwKOcnJwwmUw2Oz6tVkuxYsVwdnbm+++/56WXXnpiT+pHjx4lMDAwzfc+++wzWrZsSY0aNTCZTFZD3hkMhnTjfv3119Hr9el26BcdHZ3xA8rnpMRbCCGEECKbYmJiMJnUNt1PUtofTCYzMTEx+TOhFbmmTJkyGAwGZs6cSdu2bdmzZw9z587N9HbGjBnD0KFD8fb2pmXLliQlJXHo0CHu37+famxmWwgLC6N79+707NmTqVOnUr16dW7fvs2WLVuoUqUKrVu3ztB23nnnHSZOnEjZsmUpX74806ZNs3mS9vbbb/P111/TrVs3/vOf/1C4cGHOnTvHDz/8wIIFCzh06BBbtmyhefPm+Pv7s3//fm7fvk2FChXS3WZ4eDgzZ87Ez8+P8uXLW+bNmjWL11577YnxhISEsGXLFurWrYuLi0u6Vdqf5s6dO6xcuZLw8HASExNZtGgRK1asYMeOHZZlZsyYQalSpahUqRKJiYksWLCArVu38vvvv6fa3j///MOPP/7IkSNHAChfvjwODg4sXLiQgIAATp06Ra1atdKMpXbt2vznP//h/fff59q1a3To0IGgoCDOnTvH3LlzqVevngwnJoQQQgghMsbLywut1oHIW09e7nwUaLUOGRr7VjzbqlatyrRp05g0aRLPPfccy5cvZ8KECZneTt++fVmwYAGLFi2icuXKNGzYkMWLF+dYiTeoPXP37NmT999/n3LlytG+fXsOHjxIyZIlM7yN999/nzfeeINevXrx0ksv4enpadXe2BaCgoLYs2cPJpOJ5s2bU7lyZd599118fHxwcFC/pzt37qRVq1aEhYXxySefMHXqVF5++eV0t1m/fn3MZrNVlfLw8HBMJhPh4eFPjGfq1Kls2rSJEiVKUL169Wwd25IlS6hZsyZ169blxIkTbN++nRdeeMHyfnJyMu+//77lM3Hs2DE2b95MkyZNrLajKAr9+/dn2rRplloAOp2OxYsXM3bsWPr06cOsWbMoVqxYurFMmjSJ7777jv3799OiRQsqVarEe++9R5UqVZ6p4cQ0SgFv8R4TE4O3tzcPHjzI0//JGQwG1q9fT6tWrZ759g/5hVyz/E2uX/4n17BgiI2NZevWrTRu3Niq86D8qNOrHTl58Ff++jzt6uZmM1T+yJGKL7RjxcqVuR9gJiQkJFiSiw0bNjyxdD4vfBcTExO5cOECpUqVSjWMkngys1mtgeHl5ZU/2/M/g+Sa5a4n3V8yk2vKlRJCCCFErksZ6zooSG1PGBQUmO/Hun532HucvGpi2DI1yX6U2QzvLoWTV028O2yYfQLMBLPZzI4dO9ixY8cTO3ESQgiRMdLGWwghhBC56tGxrj/rpJaQftbJzPwt+Wus68fVq1eP2bNnM2jQIDb/o6VfQyOl/dXq5V/vcOTkVROzZ8/O8z2aA7i4uPDTTz9ZXgshhMgeSbyFEEIIkWseH+va5ODEemBQMxjSJH+NdZ2WgQMHUrlyZWZMn87w71djMpnRah3o0L4d878flm+OydHR8akdQQkhhMg4SbyFEEIIkWseH+v60QFo8ttY1+mpW7cudevWJSEhwdIOU3owF0KIZ5u08RZCCCFErihoY10/jU6no2jRovky6TaZTOzZs8fS47MQQojskRJvIYQQQuQKGes6/0hMTKRevXoA6PV6yzBCQgghskYSbyGEEELkin/Hun5yL9ky1rX9aTQaypQpY3kthBAie6SquRBCCCFyhU6no327dny9wzHVcFspzGa1B/AO7TtIabcdubm5cfbsWc6ePYubm5u9wxFCiHxPEm8hhBBC5JqCNNa1EEIIkVGSeAshhBAi16SMdT3zdw2VP3Jk9iZ1/uxNUPkjR2Zt0uSbsa6FKEi2b9+ORqMhOjra3qHkSeHh4bz77ruW6ZCQEGbMmGGZ1mg0rFmzJtfjyqqMxBsREUH79u1zJZ5ngSTeQgghhMhVAwcOZNeuXVR8oR2frFR/inyy0oGKL7Rj165dDBw40M4RisTERFq3bk3r1q1JTEy0dzgFVkREBBqNBo1Gg5OTE0WLFqVZs2Z88803mNNrj/GMSHkQ8KS/7du32ztMixs3bvDyyy/bO4wMezTeixcvotFoOHr0qE22/dVXX1GhQgV0Oh3lypXj22+/tXp/8eLFqa6lq6ur1TJTpkzB398ff39/pk6davXe/v37ef755zEajU+NRVEU5s+fT+3atfHw8MDHx4eaNWsyY8YM4uPjARg9ejTVqlXL3kFngHSuJoQQQohclzLWdWxsLFu3buX69Rt4enraOyzxkMlkYv369ZbXIue0bNmSRYsWYTKZuHXrFhs3buSdd95h5cqV/PLLLzg6Pps/1+vUqcONGzcs0++88w4xMTEsWrTIMq9w4cKW18nJyTg7O+dqjI8KCAiw276zIqfinTNnDh9++CFff/01tWrV4sCBA/Tr149ChQrRtm1by3JeXl6cPn3aMv1oJ47Hjx9n5MiRrFu3DkVRaNOmDc2bN6dy5coYjUYGDhzI/PnzM/TdeOONN1i1ahWffPIJs2bNws/Pj2PHjjFjxgxCQkJytURfSryFEEIIYTcppRyPl3YI+3J2dmbRokUsWrTIrsnMs8DFxYWAgACKFStGjRo1+Oijj1i7di0bNmxg8eLFluWio6Pp27cvfn5+eHl50bhxY44dO2a1rV9//ZVatWrh6upKkSJF6NChg+W9pUuXUrNmTTw9PQkICOD1118nKioqVTyHDx+mZs2auLm5UadOHavkCNTEKjQ0FGdnZ8qVK8fSpUst7ymKwujRoylZsiQuLi4EBQUxdOhQy/tJSUkMHz6cYsWK4e7uTu3atdMttXZ2diYgIMDyp9PpLOcqICCAuXPn8sILL7BgwQJKlSpluYc87TyllG4uXbqUkJAQvL296dq1K7GxsZZl4uLi6NmzJx4eHgQGBqYqcU3Lo1W3U0qQV61aRaNGjXBzc6Nq1ars27fPap3du3dTv359dDodJUqUYOjQocTFxVnenz17NmXLlsXV1ZWiRYvSqVOnNPetKAp+fn6sXLnSMq9atWoEBgZa7cvFxcVSyvtovKVKlQKgevXqaDQawsPDrbY/ZcoUAgMD8fX15e2338ZgMKR7HpYuXcqAAQPo0qULpUuXpmvXrvTv359JkyalOl+PXt+iRf8dZ/LUqVNUqVKFxo0b06RJE6pUqcKpU6cAmDx5Mg0aNKBWrVrpxpDip59+Yvny5Xz//fd89NFH1KpVi5CQENq1a8fWrVtp1KjRU7dhS5J4CyGEEEIIK05OTkRERBAREYGTk5O9w8k0RYG4OPv8KUr242/cuDFVq1Zl1apVlnmvvfYaUVFRbNiwgcOHD1OjRg2aNGnCvXv3APjtt9/o0KEDrVq14siRI2zZsoUXXnjBsr7BYGDcuHEcO3aMNWvWcPHiRSIiIlLt++OPP2bq1KkcOnQIR0dH3nzzTct7q1ev5p133uH999/n77//ZsCAAfTu3Ztt27YB8PPPPzN9+nTmzZvH2bNnWbNmDZUrV7asP3jwYPbt28cPP/zA8ePHee2112jZsiVnz57N0nk6d+4cP//8M6tWrbJUk37aeQKIjIxkzZo1rFu3jnXr1rFjxw4mTpxoeX/EiBHs2LGDtWvX8vvvv7N9+3b+/PPPTMf38ccfM3z4cI4ePUpYWBjdunWzVI+OjIykZcuWvPrqqxw/fpwff/yR3bt3M3jwYAAOHTrE0KFDGTt2LKdPn2bjxo00aNAgzf1oNBoaNGhgeYhx//59Tp48SUJCgiVh3bFjB7Vq1UpzlIIDBw4AsHnzZm7cuGH1udu2bRuRkZFs27aNJUuWsHjxYqsHQo9LSkpK9SBVp9Nx4MABq4Rdr9cTHBxMiRIlaNeuHSdOnLC8V7lyZc6cOcPly5e5dOkSZ86c4bnnniMyMpJFixbx2Wefpbv/Ry1fvpxy5crRrl27VO9pNBq8vb0ztB2bUQq4Bw8eKIDy4MEDe4fyRMnJycqaNWuU5ORke4ciMkiuWf4m1y//k2tYMMh1zP/ywjVMSEhQ/vnnHyUhIUFRFEXR6xVFTYFz/0+vz3jcvXr1Utq1a5fme126dFEqVKigKIqi7Nq1S/Hy8lISExOtlgkNDVXmzZunKIqivPTSS0r37t0zvO+DBw9afiPfv39f2bJliwIomzdvtizz22+/KYDlvNapU0fp16+f1XZee+01pVWrVoqiKMrUqVOVsLCwND8Lly5dUrRarXLt2jWr+U2aNFE+/PDDp8b7+LkaNWqU4uTkpERFRVnmZeQ8jRo1SnFzc1NiYmIs748YMUKpXbu2oiiKEhsbqzg7Oys//fST5f27d+8qOp1OeeeddyzzgoODlenTp1umAWX16tWKoijKhQsXFEBZsGCB5f0TJ04ogHLy5ElFURSlT58+Sv/+/a3i3LVrl+Lg4KAkJCQoP//8s+Ll5WUVZwqTyaTcv39fMZlMlnlffvmlUqlSJUVRFGXNmjVK7dq1lXbt2ilz5sxRFEVRmjZtqnz00UdPjPfIkSNW++nVq5cSHBysGI1Gy7zXXntN6dKlS6qYUnz44YdKQECAcujQIcVsNisHDx5UihYtqgDK9evXFUVRlL179ypLlixRjhw5omzfvl1p06aN4uXlpVy5csWynTlz5ihhYWFKWFiY5RiaNGmirF69WlmxYoVSqVIlpVq1asqOHTvSjaVChQrKK6+8ku77KUaNGqVUrVo13fcfv788KjO5ppR4CyGEEEIIKyaTiaNHj3L06FFp420niqJY2r0eO3YMvV6Pr68vHh4elr8LFy4QGRkJwNGjR2nSpEm62zt8+DBt27alZMmSeHp60rBhQwAuX75stVyVKlUsr1OqKqdUST958mSqEQfq1q3LyZMnAbW0OSEhgdKlS9OvXz9Wr15tKeH966+/MJlMhIWFWR3Djh07LMeQWcHBwfj5+VmmM3KeQO2R/NE+JQIDAy3HGBkZSXJyMrVr17a8X7hwYcqVK5fp+J50Lo8dO8bixYut4mzRogVms5kLFy7QrFkzgoODKV26NG+88QbLly+3VBNPS8OGDfnnn3+4ffs2O3bsIDw8nPDwcLZv347BYGDv3r2pqpBnRKVKldBqtVbHkVYThRSffvopL7/8Mi+++CJOTk60a9eOXr16AeDgoKaeL730Ej179qRatWo0bNiQVatW4efnx7x58yzbGThwIKdPn+b06dMMHDiQJUuW4OnpyUsvvUTfvn1ZvXo106ZNo2vXriQlJaUZi2KL6ic29Gz21iCEEEIIIdKVmJhI9erVAbVKqLu7u50jyhw3N9Dr7bdvWzh58qSl7a1erycwMDDN9tA+Pj6AWp03PXFxcbRo0YIWLVqwfPly/Pz8uHz5Mi1atCA5Odlq2UebFqQk/hntYb1EiRKcPn2azZs3s2nTJgYNGsTkyZPZsWMHer0erVbL4cOHrRI5AA8Pjwxt/3GPfy4zcp6AVM0nNBpNjvQi/6RzqdfrGTBggFUb+BQlS5bE2dmZP//8k+3bt/P7778zcuRIRo8ezcGDB/Hy8kq1TuXKlSlcuDA7duxgx44djB8/noCAACZNmsTBgwcxGAzUqVMnW8eQchxPOlc6nY5vvvmGefPmcevWLQIDA5k/fz6enp5WD0ke30f16tU5d+5cmu/fuXOHMWPGsHPnTvbv309YWBhly5albNmyGAwGzpw5Y9WkIUVYWJilqn1eIIm3EEIIIYSwotFoCAoKsrzObzQayGfPCqxs3bqVv/76i2HDhgFQo0YNbt68iaOjIyEhIWmuU6VKFbZs2ULv3r1TvXfq1Cnu3r3LxIkTKVGiBKC2Ic6sChUqsGfPHksJJsCePXuoWLGiZVqn09G2bVvatm3L22+/Tfny5fnrr7+oXr06JpOJqKgo6tevn+l9Z0RGztPThIaG4uTkxP79+ylZsiSgtpk+c+aMpZaArWL9559/KFOmTLrLODo60rRpU5o2bcqoUaPw8fFh69atafbErdFoqF+/PmvXruXEiRPUq1cPNzc3kpKSmDdvHjVr1kz3AVpKB4q2rN3i5ORE8eLFAfjhhx9o06aNpcT7cSaTib/++otWrVql+f6wYcMYNmwYxYsXtzxESGE0GtON+/XXX6dr166sXbs2VTtvRVGIiYnJ1XbekngLIYQQQggrbm5uXLt2zd5hPBOSkpK4efOm1XBiEyZMoE2bNvTs2ROApk2b8tJLL9G+fXu++OILwsLCuH79uqVDtZo1azJq1CiaNGlCaGgoXbt2xWg0sn79ev7v//7PUoI6c+ZMBg4cyN9//824ceMyHeuIESPo3Lkz1atXp2nTpvz666+sWrWKzZs3A+r4zCaTidq1a+Pm5sayZcvQ6XQEBwfj6+tL9+7d6dmzJ1OnTqV69ercvn2bLVu2UKVKFVq3bp3tc5mR8/Q0Hh4e9OnThxEjRuDr64u/vz8ff/xxukljVv3f//0fL774IoMHD6Zv3764u7vzzz//sGnTJmbNmsW6des4f/48DRo0oFChQqxfvx6z2fzEKu/h4eG8//771KxZ01KLoEGDBixfvpwRI0aku56/vz86nY6NGzdSvHhxXF1ds5yQnjlzhgMHDlC7dm3u37/PtGnT+Pvvv1myZIllmbFjx/Liiy9SpkwZoqOjmTx5MpcuXaJv376ptrdp0ybOnDljWb9WrVqcOnWKDRs2cOXKFbRabbrnpHPnzqxevZpu3brxySef0Lx5c/z8/Pjrr7+YPn06Q4YMkeHEhBBCCCGEeBZs3LiRwMBAQkJCaNmyJdu2bePLL79k7dq1lirZGo2G9evX06BBA3r37k1YWBhdu3bl0qVLlmGYwsPDWbFiBb/88gvVqlWjcePGlt6q/fz8WLx4MStWrKBixYpMnDiRKVOmZDrW9u3b89///pcpU6ZQqVIl5s2bx6JFiyxth318fPj666+pW7cuVapUYfPmzfz666/4+voCsGjRInr27Mn7779PuXLlaN++PQcPHrSULGdXRs5TRkyePJn69evTtm1bmjZtSr169Xj++edtEmOKKlWqsGPHDs6cOUP9+vWpXr06I0eOtNQ08fHxYdWqVTRu3JgKFSowd+5cvv/+eypVqpTuNhs2bIjJZLJqyx0eHp5q3uMcHR358ssvmTdvHkFBQWn2Ap5RJpOJqVOnUrVqVZo1a0ZiYiJ79+61qoFw//59+vXrR4UKFWjVqhUxMTHs3bvXquYEQEJCAoMHD2bevHmWBx/Fixdn5syZ9O7dm/Hjx7NkyZJ0m1loNBq+++47pk2bxpo1a2jYsCFVqlRh9OjRtGvXjhYtWmT5OLNCo+S1Vuc2llKF4MGDB2m2h8grDAYD69evp1WrVvly2I5nkVyz/E2uX/4n17BgkOuY/+WFa5iYmMiFCxesxnMWGWM2m4mJicHLy8vmpboiZ8g1y11Pur9kJteUKyWEEEIIIawkJiby2muv8dprr5GYmGjvcIQQIt+TxFsIIYQQQlgxmUysXLmSlStXynBiQghhA9K5mhBCCCGEsOLs7MysWbMsr4UQQmSPJN5CCCGEEMKKk5MTb7/9tr3DEEKIAkOqmgshhBBCCCGEEDlISryFEEIIIYQVs9lMZGQkAKGhodJzshBCZJMk3kIIIYQQwkpCQgJhYWEA6PV63N3d7RyREELkb3Z9fGkymfj0008pVaoUOp2O0NBQxo0bx6NDi2s0mjT/Jk+ebMfIhRBCCCEKNm9vb7y9ve0dhhBCFAh2LfGeNGkSc+bMYcmSJVSqVIlDhw7Ru3dvvL29GTp0KAA3btywWmfDhg306dOHV1991R4hCyGEEEIUeO7u7kRHR9s7DCGEKDDsWuK9d+9e2rVrR+vWrQkJCaFTp040b96cAwcOWJYJCAiw+lu7di2NGjWidOnSdoxcCCGEEEKIgk2j0bBmzRp7h/FEFy9eRKPRcPToUXuHIsQT2TXxrlOnDlu2bOHMmTMAHDt2jN27d/Pyyy+nufytW7f47bff6NOnT26GKYQQQgghnhEJCQncunWLhISEXNvnvn370Gq1tG7dOtPrhoSEMGPGDNsHlQERERGWZqDOzs6UKVOGsWPHYjQa7RKPEHmZXauaf/DBB8TExFC+fHm0Wi0mk4nx48fTvXv3NJdfsmQJnp6edOzYMd1tJiUlkZSUZJmOiYkBwGAwYDAYbHsANpQSW16OUViTa5a/yfXL/+QaFgwF+jomR4P+MrgVBdei9o4mU5KSkhg0aBAAs2fPxsXFJd1l88I1NBgMKIqC2WzGbDZnaRu7d+/mv/+dwdq1azGZzGi1DrRr14533x1G3bp1bRyxtQULFjB48GC++eYbrl69SlBQUKbWTzn2rEjpWym9bTzpnCqKQosWLfjmm29ISkpi/fr1DBkyBEdHRz744IMsxZNZKbFl59rnN0+7ZsK2zGYziqJgMBjQarVW72XmvqdRHu3JLJf98MMPjBgxgsmTJ1OpUiWOHj3Ku+++y7Rp0+jVq1eq5cuXL0+zZs2YOXNmutscPXo0Y8aMSTX/u+++w83NzabxCyGEEEIURImJiXTt2hVQf6+5urraOaInc3R0JCAggBIlSuDs7Jzp9RcuXMiIESOoUExLv3AjoUUh8hZ8vd2Rk9dMTJkyhTfffDMHIld7ja9QoQJbt25lwoQJVKpUiffff99qmQ0bNjB58mT++ecf3N3deemll1i2bBlt2rRhz549Vsvev3+fiRMn8ttvv7Fr1y7L/Dlz5jBnzhyOHz8OwJ9//sm4ceM4fvw4BoOBypUr8/nnn1O1alXLOoUKFWLZsmXplsQPGjSIBw8esHz5csu8jh07otfr+f333/nqq69Yvnw5ly5dwsfHh5YtWzJmzBg8PDwA9ff5hx9+yDfffMNHH33EtWvXePHFF5k1axYBAQGWbX777bd89dVXXLp0iZIlS9K/f3/69u0LwOXLl6latSo7d+6kcuXKWbkEQjxRcnIyV65c4ebNm6lqc8THx/P666/z4MEDvLy8nrgdu5Z4jxgxgg8++MByY69cuTKXLl1iwoQJqRLvXbt2cfr0aX788ccnbvPDDz/kvffes0zHxMRQokQJmjdv/tSTYU8Gg4FNmzbRrFkznJyc7B2OyAC5ZvmbXL/8T65hwVCgrqPZBIk3IfY8GKLBubD6b6Eq4FbC3tFlSnJyMhMmTACgTZs2T0xm88I1TExM5MqVK3h4eGT6IcHu3bsZMWIEQ5orTO9h5NEhy4e2MPLuUhg+fDi1atXKkZLvlStXUr58eZ5//nkiIiJ47733GD16NBqNBoDffvuNN954g48++oilS5eSnJzMhg0b8PLyYs2aNVSvXp1+/fpZElEvLy9cXFzQarVWv31dXV1xcHCwzDObzfTu3Zvnn38evV7P/Pnz6dKlC6dPn8bT09Oynk6nS/c3tJOTE46Ojlbve3h4WJIQNzc3Zs6cSalSpTh//jyDBw9m/PjxfPXVV5aYEhISmDNnDkuXLsXBwYGePXsyduxYli1bBsDy5cuZOHEiX375JdWrV+fIkSMMGDAAX19fevXqZUni3d3d8/RvfVtSFIXY2Fg8PT0tnxORcxITE9HpdDRo0CDV/SWldnVG2DXxjo+Px8HBupm5VqtNs8rEwoULef75562ewqXFxcUlzepQTk5O+eI/9PwSp/iXXLP8Ta5f/ifXsGDI19dRUSDpLugjIeE6OLqDriRoNGCOBkct5LNjc3JyynRVYXteQ5PJhEajwcHBIdVvy6f58r8zqFBcmyrpBnBwgBlvwJaTWr7873+pX7++DaNWLVq0iB49euDg4ECrVq3o06cPu3btIjw8HIAJEybQtWtXxo4da1mnevXqABQpUsSSYD9aPT0lGXv0XDw+r2nTpoCagMfExDBv3jwKFy7Mrl27aNOmzSPnIP1zmtK+28HBAUVR2LJlC7///jtDhgzBwcGBYcOGWZYtXbo0n332GQMHDmTOnDmWbRsMBubNm0doaCgAgwcPZuzYsZZ9jhkzhqlTp9KpUycAQkNDOXXqFF9//TW9e/e2LJeVa59fpeRKKede5CwHBwc0Gk2a97jM3PPsmni3bduW8ePHU7JkSSpVqsSRI0eYNm1aqqo8MTExrFixgqlTp9opUiGEEEKINBjj1BLu+MtqAq4LAge7/rwSmZCQkMCatWuZ0s2cKulO4eAA/RoaGf79ahISEtDpdDbb/+nTpzlw4ACrV68G1CrzXbp0YeHChZbE++jRo/Tr189m+0xx69YtPvnkE7Zv386tW7cwm83Ex8dz+fLlTG1n3bp1eHh4YDAYMJvNvP7664wePRqAzZs3M2HCBE6dOkVMTAxGo5HExETi4+MtTUDd3NwsSTdAYGAgUVFRAMTFxREZGUmfPn2szoHRaJQx5kW+Y9f/GWbOnMmnn37KoEGDiIqKIigoiAEDBjBy5Eir5X744QcURaFbt252ilQIIYQQ4hFmA8RdVUu5jbHgUgQcC05fMmazmRs3bgBqIlRQS9ViYmIwmcyEPqXvu9L+YDKpJcO2TLwXLlyI0Wi0Kq1WFAUXFxdmzZqFt7d3lvaXUgL9qMc7gerVqxd3795l+vTp+Pr64uvrS926dUlOTs7Uvho1asScOXNwdnYmKCgIR0c1vbh48SJt2rThrbfeYvz48RQuXJjdu3fTp08fkpOTLYn34yWGGo3GErterwfg66+/pnbt2lbLPd7JlRB5nV0Tb09PT2bMmPHUIRD69+9P//79cycoIYQQQoj0KAokRkHsOUiKAicvtf12AWtnmZCQQPHixQE1+XF3d7dzRDnDy8sLrdaByFtP7hn6fBRotQ42bUNsNBr59ttvmTp1Ks2bN7d6r3379nz//fcMHDiQKlWqsGXLFnr37p3mdpydnTGZTFbz/Pz8uHnzJoqiWKqYPz7O9Z49e5g9ezatWrUiJiaGBw8ecOfOnUwfh7u7O2XKlEk1//Dhw5jNZqZOnWp5cPPTTz9lattFixYlKCiI8+fPpzvqkRD5hdSFEkIIIYTICEMM6M9D3BXQOIBbMdAU3FK3lJLLgkyn09G+XTu+3vErQ1ukbuMNYDbD1zsc6dC+nU1Lu9etW8f9+/fp06dPqmrTr776KgsXLmTgwIGMGjWKJk2aEBoaSteuXTEajaxfv57/+7//A9RxvHfu3EnXrl1xcXGhSJEihIeHc/v2bb744gs6derExo0bLR2ypShbtixLly6lRo0a3Lhxg7Fjx9r0+MqUKYPBYGDmzJm0bduWPXv2MHfu3ExvZ8yYMQwdOhRvb29atmxJUlIShw4d4v79+1YdKguR1xXMekNCCCGEELZiSoKYs3B7H+gvgkth0AUU6KTb3d0dg8GAwWAosKXdKd4d9h4nr5oYtkxNsh9lNsO7S+HkVRPvPtJRmC0sXLiQpk2bptlW+dVXX+XQoUMcP36c8PBwVqxYwS+//EK1atVo3LgxBw4csCw7duxYLl68SGhoKH5+fgBUqFCB2bNn89VXX1G1alUOHDjA8OHDU+3//v371KxZk4EDBzJ48GD8/f1tdnxVq1Zl2rRpTJo0ieeee47ly5dbesrPjL59+7JgwQIWLVpE5cqVadiwIYsXL6ZUqVI2i1WI3GDXcbxzQ0xMDN7e3hkaW82eDAYD69evp1WrVvm3V9dnjFyz/E2uX/4n17BgyNPXUTFDwo2H1crvgkshtWp5ZsRdgcLVwT04Z2LMA/LCNUxMTOTChQuUKlUqS2OOz507l0GDBlGhuJZ+DY2U9lerl3+9w5GTV03Mnj2bgQMH5kDk9pfSq7mXl1eBbctf0Mg1y11Pur9kJtcs+HWIhBBCCCEyK+me2nFa/HXQuoB7CbV6uSiQBg4cSOXKlZkxfTrDv1+NyWRGq3WgQ/t2zP9+WI6M3y2EeLZI4i2EEEIIkcKYAPoLEH9R7blc5w8OzvaOKtclJSVZ2s9OmzYNFxcXO0eU8+rWrUvdunVJSEiwlCbass2zEOLZJom3EEIIIYTZCAnXIfYsJD8AV19w9LB3VHZjNBqZPXs2AF988cUzkXin0Ol0knALIWxOEm8hhBBCPLsUBZLuqNXKE26qY3G7lyxww4NllpOTE6NGjbK8FkIIkT2SeAshhBDi2WTQP6xWfklNwHWB4CA/jUAdG3r06NH2DkMIIQoM+d9FCCGEEM8Ws0HtbVwfCUY9uPiBo1QtFkIIkXMk8RZCCCHEs0FRIPHWw+HBosDJW61WnlNMiXDtF/CukHP7yCGKovDgwQMAvL290TzjVe+FECK7JPEWQgghRMGX/ABiz0PCFbU6uVtx0GhzZl9mI1xbB+fmQdJtcPWHahNzZl85JD4+nkKFCgGg1+txd3e3c0RCCJG/SeIthBBCiILLlPiwWvl5MCWoSbA2h3roVhSI2gFnvoK4C+o8F39wD86Z/QkhhMg3HOwdgBBCCCGEzZlNEH8N7uyH6L/UZNu9RM4l3fePwf6+cGS4mnQ7eUP596DmLAhqlTP7zEFubm4kJyeTnJyMm5ubvcMRdqLRaFizZo29w8iQ7du3o9FoiI6OtncoQqRJEm8hhBBCFCxJ9+D+n3D3kFri7V4CnDxzZl/6C/DncNjfB6KPgYMLlO4NDdZCyOvgkD+H4tJoNDg5OeHk5PRMtu82GAy5ur99+/ah1Wpp3bp1ptcNCQlhxowZtg8qAyIiItBoNJbPS9GiRWnWrBnffPMNZrPZLjEJkVdJ4i2EEEKIgsEYD9H/wN0/IOEG6IqCaxHQ5MDPncTb8Pd42N0ForYDDlC8PTRYDWFvg5OH7fcpcsXevXvx8/Nn3759ubbPhQsXMmTIEHbu3Mn169dzbb+20LJlS27cuMHFixfZsGEDjRo14p133qFNmzYYjUZ7hydEniGJtxBCCCHyN7MR4i7DnX0QcwocPcCtWM6UNhv0ahvune3h6mrADP4Nod6P8NwnahvyAiA5OZkRI0YwYsQIkpOT7R1Orvr445E8eBDNxx+PzJX96fV6fvzxR9566y1at27N4sWLUy3z66+/UqtWLVxdXSlSpAgdOnQAIDw8nEuXLjFs2DBLyTPA6NGjqVatmtU2ZsyYQUhIiGX64MGDNGvWDH9/f0qWLEmjRo34888/Mx2/i4sLAQEBFCtWjBo1avDRRx+xdu1aNmzYYHUs0dHR9O3bFz8/P7y8vGjcuDHHjh3L0HECLF26lJo1a+Lp6UlAQACvv/46UVFRqeI5fPgwNWvWxM3NjTp16nD69Gmr9+fMmUNoaCjOzs6UK1eOpUuXWt5TFIXRo0dTsmRJXFxcCAoKYujQoZb3k5KSGD58OMWKFcPd3Z3atWuzffv2TJ8z8WySxFsIIYQQ+ZOiqCXPdw/C3cOgmNXhwRxzoAduczJc/A52toPzi8CcBD5VoPYCqDEVPErZfp92ZDAYmDJlClOmTMn1atf2tGvXLrZv3wK8wbZtm9m9e3eO7/Onn36ifPnylCtXjh49evDNN9+gKIrl/d9++40OHTrQqlUrjhw5wpYtW3jhhRcAWLVqFcWLF2fs2LHcuHGDGzduZHi/sbGx9OrVi507d7Jp0ybKlClDq1atiI2NzfYxNW7cmKpVq7Jq1SrLvNdee42oqCg2bNjA4cOHqVGjBk2aNOHevXtPPU5QP5Pjxo3j2LFjrFmzhosXLxIREZFq3x9//DFTp07l0KFDODo68uabb1reW716Ne+88w7vv/8+f//9NwMGDKB3795s27YNgJ9//pnp06czb948zp49y5o1a6hcubJl/cGDB7Nv3z5++OEHjh8/zmuvvUbLli05e/Zsts+ZKPikV3MhhBBC5D+GWLV9dfxlddotSB0mzNYUM9z4H5ydAwkPqwC7h0DYYLWku4C2f3ZycmL48OGW18+KkSPHoNVWwWRahFZ7lJEjx7B166Yc3efChQvp0aMHoFbbfvDgATt27CA8PByA8ePH07VrV8aMGWNZp2rVqgAULlwYrVZrKQXOjMaNGwNgNpuJiYlh3rx5FC5cmB07dtCmTZtsH1f58uU5fvw4ALt37+bAgQNERUXh4qJ2cDhlyhTWrFnDypUr6d+//xOPE7BKoEuXLs2XX35JrVq10Ov1eHj827Rj/PjxNGzYEIAPPviA1q1bk5iYiKurK1OmTCEiIoJBgwYB8N577/HHH38wZcoUGjVqxOXLlwkICKBp06Y4OTlRsmRJS/J/+fJlFi1axOXLlwkKCgJg+PDhbNy4kUWLFvH5559n+5yJgk1KvIUQQgiRf5iSITYS7vwB+khw8gFdYM4k3Xf+gL094PinatLt4geVPoG6P0DR8AKbdAM4OzszefJkJk+ejLOzs73DyRUppd0m0yhAi8k0KsdLvU+fPs2BAwfo1q0bAI6OjnTp0oWFCxdaljl69ChNmjSx+b5v3bpFv379KFeuHCVLlsTHxwe9Xs/ly5dtsn1FUSxV348dO4Zer8fX1xcPDw/L34ULF4iMjASefpyHDx+mbdu2lCxZEk9PT0ty/Xi8VapUsbwODAwEsFRJP3nyJHXr1rVavm7dupw8eRJQS+UTEhIoXbo0/fr1Y/Xq1ZZ26n/99Rcmk4mwsDCrY9ixY4flGIR4EinxFkIIIUTep5gh8ZaadCfdBicvtVp5TnhwEs7MhLsH1GlHdyjVS+2lXOuaM/sUdvdvaXf7h3M6oNVWztFS74ULF2I0Gi0lqKAmrC4uLsyaNQtvb290Ol2mt+vg4GBVXR1S99Teq1cv7t69y/Tp0/H19cXX15e6devarE3/yZMnKVVKbYKh1+sJDAxMsz20j48PwBOPMy4ujhYtWtCiRQuWL1+On58fly9fpkWLFqnifbSGRkrin9Ee1kuUKMHp06fZvHkzmzZtYtCgQUyePJkdO3ag1+vRarUcPnwYrVZrtd6jJe5CpEcSbyGEEELkbcnREHsBEq6oJdtuxUCjfepqmRZ/Va1SfuN/6rTGEUq+BqF9wNnH9vvLwxRFsZT0OTo6Fvghxf5t2/0z/1YIdXhY6t2J3bt3U69ePZvu02g08u233zJ16lSaN29u9V779u35/vvvGThwIFWqVGHLli307t07ze04OztjMpms5vn5+XHz5k2rUuejR49aLbNnzx5mz55Nq1atiImJ4cGDB9y5c8cmx7Z161b++usvhg0bBkCNGjW4efMmjo6OVh28PepJx3nq1Cnu3r3LxIkTKVGiBACHDh3KdFwVKlRgz5499OrVyzJvz549VKxY0TKt0+lo27Ytbdu25e2336Z8+fL89ddfVK9eHZPJRFRUFPXr18/0voWQxFsIIYQQeZMpEeIugf6i+trVD7Qutt9P8n2IXAiXV4LycPijwJeh7EA1yX8GxcfHW0rx9Ho97u450GFdHpK6tDtFzpV6r1u3jvv379OnTx+8vb2t3nv11VdZuHAhAwcOZNSoUTRp0oTQ0FC6du2K0Whk/fr1/N///R+gjuO9c+dOunbtiouLC0WKFCE8PJzbt2/zxRdf0KlTJzZu3MiGDRvw8vKy7KNs2bIsXbqUGjVqcOPGDcaOHZul0vWkpCRu3ryJyWTi1q1bbNy4kQkTJtCmTRt69uwJQNOmTXnppZdo3749X3zxBWFhYVy/ft3SoVrNmjWfeJwlS5bE2dmZmTNnMnDgQP7++2/GjRuX6VhHjBhB586dqV69Ok2bNuXXX39l1apVbN68GYDFixdjMpmoXbs2bm5uLFu2DJ1OR3BwML6+vnTv3p2ePXsydepUqlevzu3bt9myZQtVqlTJ0hjs4tkibbyFEEIIkbeYTWrp850/4MEJNdl2L277pNuYAJELYEd7uPSDmnT7vgh1lkHVcc9s0v2ssW7b/fhPY4cca+u9cOFCmjZtmirpBjXxPnToEMePHyc8PJwVK1bwyy+/UK1aNRo3bsyBAwcsy44dO5aLFy8SGhqKn58foJbszp49m6+++oqqVaty4MABS2d5j+7//v371KxZk4EDBzJ48GD8/TM/HN7GjRsJDAwkJCSEli1bsm3bNr788kvWrl1rqZKt0WhYv349DRo0oHfv3oSFhdG1a1cuXbpE0aJFAZ54nH5+fixevJgVK1ZQsWJFJk6cyJQpUzIda/v27fnvf//LlClTqFSpEvPmzWPRokWWjux8fHz4+uuvqVu3LlWqVGHz5s38+uuv+Pr6ArBo0SJ69uzJ+++/T7ly5Wjfvj0HDx6kZMkcavYiChSN8ngDkAImJiYGb29vHjx4YPWUL68xGAysX7+eVq1aPVO9h+Zncs3yN7l++Z9cw4Ih1XVMugv68xB/XW1P7VIYNDYuJzAb4eoaiPxa3R+AV3kIGwJFatt2X3FXoHB1cA+27XZzmKIoPHjwAABvb+8nVjXPC9/FxMRELly4QKlSpXB1zVw7/EaNmrJjx1EUZQlpl0mZ0Wh6ER5ePcd7OLeHlF7Nvby8cHCQMrn8QK5Z7nrS/SUzuaZUNRdCCCGE/RkTIO4MxF0ExQS6ouBg4yROUeDWVjjz1b/DkOmKQdm3ILC57RP8fEyj0Vg6vSrITCYT+/fvQ1HigfSH0FIU+OOPvZhMplQdawkhREZI4i2EEEII+zE/bFN99wCYY8C1iNqLuK3dOwKnv4QHf6nTTj4Q2hdKvmr7BF/kG1qtlps3bxAbG/vUZT09PSXpFkJkmSTeQgghhMh9iqIOC3b/7MMZZnV4MFv3nh0bCWdmwe1d6rTWFUJ6QKke4ChDAKUnOTmZzz//HICPPvqoQI/l7eXllaebIwohCgZJvIUQQgiRuwz6h+24L4PpYVczzoVsm3Qn3oKzc+Hab4BZHX6seHsI7aeWqosnMhgMjBkzBlB7gi7IibcQQuQGSbyFEEIIkTvMBrWzMX0kGPXg6g+KM3DddvswxMD5xXDpRzAnqfOKNoayg8AjxHb7KeAcHR0ZNGiQ5XV+UcD7DBZC2IGt7iv5504qhBBCiPxJUdQS6NhzkBQFTt5qtXIAo9k2+zAlweWf4PwiNfkGKFQdyg0Fn8q22UdmGOMg6Z5atd0hB8Yez2EuLi589dVX9g4jw1J6U4+Pj8/SWNRCCJGe+Ph4gGyP2iCJtxBCCCFyTvIDiD0PCVfU6t5uxdV/bUUxwfUNarXyxJvqPI/S6tBgfvVs32b8aYx6SLqvJtweoeBeApx9cjeGZ5BWq8XHx4eoqCgA3NzcnjgEmviX2WwmOTmZxMREGZoqn5BrljsURSE+Pp6oqCh8fHyy3bmiJN5CCCGEsD1TEsRdVttymxLA1U9NRm1FUeDOHjg9C/Tn1HmuRaHMACjW2rbJfUYYYiH5PmjdwLOs+oDB2Tt3Y3jGBQQEAFiSb5ExiqKQkJCATqeThxX5hFyz3OXj42O5v2SHJN5CCCGEsB3FDAk3IfYsJN0Fl0K278ws+m84MxPuHVanHT2gdG8I7mLb5D4jDDFqCbejO3iWB/fi4OSZuzHkgLi4OMs43tHR0bi758AQbzam0WgIDAzE398fg8Fg73DyDYPBwM6dO2nQoEG2q9KK3CHXLPc4OTnZbBhBSbyFEEIIYRvJ99Vq5fFXQeuiVrPW2LAaZNxlODsbbm5Wpx2coWQXKB2Ru6XLiqIm3MnRatLvUwl0xcCpYA1PZjQa7R1Clmi1WhlvOxO0Wi1GoxFXV1dJ4vIJuWb5kyTeQgghhMgeUyLoL0LcBTAlg85fTYptJekuRC6AK6vUNt1oIKgVlB0IukDb7edpFAUMD9Q/Ry+10za3ILW0u4DR6XRcvXrV8loIIUT2SOIthBBCiKwxmyDxhtpbefI9cPZVhwizFWMcXFgGF5ep7cQBitSBckPUdtS5RVHAEA3JMWqP7N5VHibcbrkXQy5zcHCgWLFi9g5DCCEKDEm8hRBCCJF5SXchNhISroOjDtxK2q4HcbNRLd2OXKAm9ADeFSFsKPjWtM0+MkIxq9XJDbFqVfZC1dQSdkcpARZCCJE5kngLIYQQIuOM8aC/AHEX1WrfugBwsFEbQ0VR22+fnQ3xV9R5biUg7G0o2iT3hgZTzGp7daMenAtD4RrqceZ2x212lJyczH//+18A3nnnHZydbdh0QAghnkGSeAshhBDi6cxGSLj2sFp5DLj62rRts+beIYicBQ/+UWc4F4Yy/aB4B3DIpZ8rikntodwU/zDhLgeuAWpHcc8Yg8HAf/7zHwAGDRokibcQQmSTJN5CCCGESJ+iQNIdNeFOuKn23O1ewnalz7FneTFxKo5//qlOa3UQ0gNK9ci9TsvMxocl3AngUlit1u5aFLTPbrLp6OhIr169LK+FEEJkj9xJhRBCCJE2gx705yH+sjrtFmS70ueEm3B2Do7X11MUBUWjRVOiI4T2BRdf2+zjacxGtQ25KQlcioDPc2rCbauq8/mYi4sLixcvtncYQghRYEjiLYQQQghrZgPEXQF9pNrO2cXPdh2KJUfD+cVw+ScwJ6MBrmnr4l97GE5eIbbZx9OYjWopvtkIrn7gE/ww4ZafRUIIIXKG/A8jhBBCCJWiQGKUWq086ZY6dJZ7Sdts25QIl35Qk26jXp1X+HmMoUM49I8PrdyCbLOfJzEb1N7YzUZ12DP3YPVfSbiFEELkMPmfRgghhBBgiFGrlcddBo0W3Iqr/2aXYoJr6+DsPEiKUud5lFHH4i5SB8WkANezv58nMSerCbdifphwh6il+A42OL4CKi4uzjKO97Vr13B3T7+9fWJiouVfJyeppi+EEGlxsHcAQgghhLAjUxLEnIPb+yD2gtq+WheQ/aRbUSBqJ+zpBn+PU5Nu1wCoPBrqLge/ujk/PJgpCeKvQeJtcPEH39rg+8LDIdAk6X6aBw8e8ODBg3Tf3717N51e7UhQUCAAQUGBdHq1I3v27MmtEIUQIt+QEm8hhBDiWaSY1Q7O9JFqYursAx42qlZ+/zicmQn3j6jTTl5Q+k0o+VruDM1lSlRLuNGALlCtUu5SBDRS3pBROp2OM2fOWF4/bs6cObz99ttUKK7ls05qKfdnnczM3/Ir9euvYfbs2QwcODBXYxZCiLxMEm8hhBDiWZMcDbGREH9VHTLLvYRtklL9RTj7Fdzapk47uEBwVyjdS02+c5opUe00TaMFXbGHCbdvzpesF0AODg6ULVs2zfd2797N22+/zZDmCtN7GDE5OLEeGNQMhjQx8u5SdezvypUrU7du3dwNXAgh8ihJvIUQQohnhSkR4i6B/oJaDVvnDw42GKs68Q5Ezoera9U23ThAsTZQpr9arTunGRPUEm4HR9CVVEvunQtLwp1DZkyfRoXiWqb3MOLgAKZH3nNwgBlvwJaTWmZMny6JtxBCPCSJtxBCCFHQmU2QeEPtrTz5Hjj7qsNoZZdRDxeWwsXlalIP4Fcfwt4GzzLZ3/5T9x8HSffUUnuPYHArCc6FJOG2AYPBwPz58wHo37+/pdO0hIQE1qxdy5RuZhzSqSTh4AD9GhoZ/v1qEhIS0qyqLoQQzxpJvIUQQoiCLOme2o47/hpodeBmg2rlZgNc/hkiF4AhWp3nXVntqbxwjWyH/FRGPSTdV9uLe4SCe3E14RY2k5yczODBgwGIiIiwJN4xMTGYTGZCiz55/dL+YDKZiYmJkcRbCCGQxFsIIYQomIzxapvr+IvquNW6AHDI5lBPihlu/A5n50DCNXWeW0kIGwxFG+V8SbNBr5bYa93As6w65Jmzd87u8xml1Wrp1KmT5XUKLy8vtFoHIm+Zn7j++SjQah3w8sqFtv1CCJEPSOIthBBCFCRmIyRch9izkPwAXIuAY/pjMGfYnf1qT+Uxp9RpF18I7Q/F26ltq3OSIUYt4XZ0B89yagl3bnTW9gxzdXVlxYoVqebrdDrat2vH1zt+ZWgLY5rVzc1m+HqHIx3at5PSbiGEeEgSbyGEEKIgUBS1R299pDpMmKMbuJfMfil0zCk4PQvu/qFOa92h9BsQ3B0cczCpUhQ14U6OBkcP8K4IbsXAyTPn9iky5N1h79GgwRqGLYPpPYBHkm+zGd5dCievmpj//TC7xSiEEHmNJN5CCCFEfmfQqz2Vx19Wq4PrArNfCh1/Dc7OhRsb1GmNI5TsBKF9crY9taKA4YH65+gFPs+pCbctSu2FTdSrV4/Zs2czaNAgNv+jpX8TCGkPszfB/C2OnLxqYvbs2dKjuRBCPEISbyGEECK/MhvUBDn2HBhjwcUv+6XQydEQuRAurwTFoM4LbAFl31LbVOcURYHk+5AcA07e4F0F3ILUknuR6+Lj4y3jeJ89exY3N+vrMHDgQCpXrsyM6dP5ZOVGlrWHT1Y60LJFO+Z/P0ySbiGEeIwk3kIIIUR+oyiQGKVWK0+8pbZ3diuRvWrlpkS4+B1cWKIO0wXg+wKEDQXv8raJOy3Kw0664q+BzgsKVQVdUM5WYxdPpSgK169ft7xOS926dalbty6xsbFs3bqV69dv4OkpTQGEECItkngLIYQQ+YkhBvTnIe4yaLRqkpqdauVmI1z7Fc7NU9uIA3iGQbmhUORF28ScFsWslq4nxgJaKFQZPIuD1jXn9ikyzNXVlSNHjlheP23ZjCwnhBDPMkm8hRBCiPzAlAzxVyA2Ekzx4OqXvSRVUSBqB5yZBXEX1Xm6ILVKeWCL7I/1ne5+Hybchlhw9lFLuPkb3INBm83hzoTNaLVaqlWrZu8whBCiwJDEWwghhMjLFLNanTz2HCTeVpNV1xLZ2+b9o3D6S4g+rk47eaudppXsBA7O2Y04bYpZ7TAtOUY9hsI11LHFzVrg75zZpxBCCJFHSOIthBBC5FXJ0RD7sLdyrbM6frVGm/Xt6c+rJdxRO9VpBxcIeR1K9QInD5uEnIqigCH634S7UDW107SU0nqzIWf2K7LFYDCwfPlyALp3746Tk9RGEEKI7JDEWwghhMhrjAkQd0mtAm5Kelit3CXr20uMUttwX/0VMAMOULwdlOmvbjsnWCXc3qkTbpGnJScn07t3bwBee+01SbyFECKbJPEWQggh8gqzERKuq9XKDdHg7Ju9xNgQCxe+VXsrNyep8/zDIext8Chli4hTk4S7QNBqtbRq1cryWgghRPZI4i2EEELYm6JA0m2147TEW+rY1W4lsz48mDkZLq+AyG/UdtUAPlXVnsoLVbVd3I+ShLtAcXV15bfffrN3GEIIUWBI4i2EEELYkyEG9BceDg+mAV1g1ocHU8xwYyOcmQOJN9R57qWg3GDwa5C9cb7T3ack3EIIIcTTSOIthBBC2IMpCeKugD4STAnZGx5MUeDOH3BmJsSeUee5+EHZARDUJnvjfD9pn4YHkPzgYcJdFdyKScIthBBCpEESbyGEECI3mU2QeFNtx510F1wKgWuRrG/vwUl1aLB7B9VpR3co3RuCu+ZMEpxWwq0LAked7fcl7CY+Pp6qVdVmCceOHcPNzc3OEQkhRP4mibcQQgiRW5Luqu24E26oSbF7CdA4ZG1b8VfhzGy4+bs6rXGCkq9B6JvqsF229mjC7SQJd0GnKArnzp2zvBZCCJE9kngLIYQQOc0Y93A87ktqO2xdUXDI4vBMSfcgciFc+RkUI6CBoJZQ5i21bbWtWRLuaHDykYT7GeHq6sru3bstr4UQQmSPJN5CCCFETjElqyXT+vNgjAWXImqP5VlhjFeHBbvwLZji1XlFXoKwweBVznYxp0hJuA0PwPFhp2mScD8ztFotdevWtXcYQghRYEjiLYQQQtiaYlaHBYuNhKQotWq2W4ms9SpuNsLVNXDua0i+q87zqgDlhoDvCzYNG0idcPtICbcQQgiRXZJ4CyGEELaUfB9iz6sl3VoncCsOGm3mt6MocGsrnPkK4i+r83TFIOxtCGia9bbhT9rfowm3dxW1l3JJuJ9JRqOR1atXA9ChQwccHeUnoxBCZIfcRYUQQghbMMarY3HHXVCrmLv6gdYla9u696faU/mDv9VpJx8o0xdKvJr1tuHpsUq4vR4m3EFZrxIvCoSkpCQ6d+4MgF6vl8RbCCGySe6iQgghRHaYjZBwTR0eLPkBuPqCq3/WthV7Ti3hvr1Lnda6QkgPKNUDHD1sFzNIwi2eyMHBgYYNG1peCyGEyB5JvIUQQoisUBRIuv1weLCb4OQB7iWz1o474SacmwfXfgPMatX04u2hTD+1QzZbxy0Jt3gKnU7H9u3b7R2GEEIUGJJ4CyGEEJlliFF7Ko+7rCbJbkHgkIX/Ug0xcH4xXPoRzEnqvKJNIGwQuAfbNGQ14Y55mHB7SsIthBBC5CJJvIUQQoiMMiWqybb+ApgSHrbjzsIYx6YkuPwTnF+kJsMAhWpAuaHg85xtY05JuJOjwckLvJ972GmaJNxCCCFEbrFrox2TycSnn35KqVKl0Ol0hIaGMm7cOBRFsVru5MmTvPLKK3h7e+Pu7k6tWrW4fPmynaIWQgjxzDGb1F7K7/wB0X+D1hncS2Q+6VZMcG0d7OoIp/+rJsQeoVBjBrwwz7ZJt6Kobc7jLqv79akMfnXAq6wk3eKpEhISqFatGtWqVSMhIcHe4QghRL5n1xLvSZMmMWfOHJYsWUKlSpU4dOgQvXv3xtvbm6FDhwIQGRlJvXr16NOnD2PGjMHLy4sTJ07g6pqFEgYhhBAiMxQFku6CPhISboBWpybcmR3KS1Hgzh44PQv059R5rkWhzEAo1iprw409aV+WEm5PNeGWEm6RSWazmWPHjlleCyGEyB67Jt579+6lXbt2tG7dGoCQkBC+//57Dhw4YFnm448/plWrVnzxxReWeaGhobkeqxBCiGeMQa9WKY+/DIoZdIFZa8cd/bc6NNj9P9VpR08I7Q0lO2etmnp6UiXcKVXK3W23D/HMcHV15ffff7e8FkIIkT12rWpep04dtmzZwpkzZwA4duwYu3fv5uWXXwbUJ6y//fYbYWFhtGjRAn9/f2rXrs2aNWvsGLUQQogCzZSs9lR+Z59aOu3knbXO0+Iuw5H/gz8i1KTbwRlKvQEN1kCpnrZLulNVKX/uYZXyMEm6RZZptVqaNWtGs2bN0GptWCNDCCGeUXYt8f7ggw+IiYmhfPnyaLVaTCYT48ePp3v37gBERUWh1+uZOHEin332GZMmTWLjxo107NiRbdu2WcaXfFRSUhJJSUmW6ZgYtdMag8GAwWDInQPLgpTY8nKMwppcs/xNrl/+Z/NrqJghMUot5U66o3ZE5lJcfc+Yiaq2SXdxuLAAh2tr0CgmFDQoga0xhfYH14DMb+9JDLEPS7g9wKM86B5WKVeAfPLZlu9i/ifXMH+T65f/yDXLOzJzDTTK4z2Z5aIffviBESNGMHnyZCpVqsTRo0d59913mTZtGr169eL69esUK1aMbt268d1331nWe+WVV3B3d+f7779Ptc3Ro0czZsyYVPO/++473NykfZsQQoic4agkEGpYQxnDWhxJBOCm9nn+cX6DWIcQ+wYnRCaZTCaOHDkCQPXq1aXUWwgh0hAfH8/rr7/OgwcP8PLyeuKydk28S5QowQcffMDbb79tmffZZ5+xbNkyTp06RXJyMu7u7owaNYpPPvnEssz//d//sXv3bvbs2ZNqm2mVeJcoUYI7d+489WTYk8FgYNOmTTRr1gwnJyd7hyMyQK5Z/ibXL/+zyTU0JkDcJUi4DGYjuBRRq4RnhtmAw7U1OFxYiCb5njrLqxLmMoNRCj+ftbjSY4hVq5U7uqmdvOnyf6dp8l3Mm+Li4ihUqBAA9+/fx909/WYLcg3zN7l++Y9cs7wjJiaGIkWKZCjxtmtV8/j4eBwcrJuZa7VaS++Zzs7O1KpVi9OnT1stc+bMGYKDg9PcpouLCy4uLqnmOzk55YsPZn6JU/xLrln+Jtcv/8vSNTQbIOE6xJxTOyRzLQyOHpnbhqLAzc1w9it1qDEAt5IQNgiHok1w0Ggyt70nMcRA0n01Rt+KasLtlMl48zj5LuYtLi4u1KxZ0/I6I9dGrmH+Jtcv/5FrZn+ZOf92Tbzbtm3L+PHjKVmyJJUqVeLIkSNMmzaNN99807LMiBEj6NKlCw0aNKBRo0Zs3LiRX3/9le3bt9svcCGEEPmTojxsxx0JCTfB2evh8GCZTJLvHlJ7Ko/5R5129oUy/aB4+6z1fJ4eQywk3VMTbp9KBTLhFnmTTqfj4MGD9g5DCCEKDLsm3jNnzuTTTz9l0KBBREVFERQUxIABAxg5cqRlmQ4dOjB37lwmTJjA0KFDKVeuHD///DP16tWzY+RCCCHyneQHEHseEq6q43C7Fct8khx7Fk7PhDt71Wmtm9pTeUh321b5NsRC8n11+94Vwa24JNxCCCFEPmbXxNvT05MZM2YwY8aMJy735ptvWpWCCyGEEBlmSlTbcesvgikBXP0yP5RXwg04OweubwAU0GihREcI7QsuvraL1aCH5Htqwu1VQRJuIYQQooCwa+IthBBC5BizSW3HrY9Uk1nnwuBaJHPbSI6G84vh0o+gPBwyJKAZlB2kVlG3FaNerVKudQPPcuq2nTxtt30hMikhIYGmTZsCsHnzZnQ6nZ0jEkKI/E0SbyGEEAWLoqjjcOsj1ZJqRze107PMtOM2JcKlH9Sk26hX5xWuCeWGgHcl28VqjHuYcLuCZ9jDhDvvjsAhnh1ms5m9e/daXgshhMgeSbyFEEIUHIZY0F+A+MtqAq4Lylw7bsUE19bB2XmQFKXO8ywLYUOgyEuZ74QtPcY4SLwLjq7q9t2Kg7O3bbYthA24uLiwevVqy+snMhtyISIhhMjfJPEWQgiR/5mS1CG9YiPBFAcufuCYiaqxigK3d8GZWaA/r85zDYCyb0HQy2pnbLZgjIeku6B1Ac8y4F5SEm6RJzk6OtK+ffuMLZx4S/03/ip4lgQHbY7FJYQQ+ZUk3kIIIfK3hJuQcF5NaJ19wLVk5ta/fxzOzIT7R9RpJ28o3RtKvqYmyLZgTHiYcDuBR+mHCbePbbYthN0p6j/3j4HxHniFSR8FQgjxGEm8hRBC5D+KonaYBnDvT3B2eTgedyZKpvUX4exXcGubOu3gAsHdoHQv2yUNKQm3gyN4hDxMuAvZZttC5CCTycSuXbsAqF+/PlptBkqxXf0g/oo6FJ5XmNqEwla1RYQQIp+TxFsIIUT+YohRk+bYy+q0q5+aeGdU4h2InA9X16ptunGA4m2hTH9wLWqbGE2J6n4cHMEjGNyDJeEW+UpiYiKNGjUCQK/X4+7u/vSVHJzVB2BJ99QHYol3wausDIknhBBI4i2EECK/MCaonaaljMftWBi4Dw5OGVxfD+e/hUvfqYkxgH8DKPs2eIbaJkZTotqjusZR7Und42HCbatO2YTIJRqNhooVK1peZ4pLYTXZjr+k1kzxCgO3YlL6LYR4pkniLYQQIm8zGyD+mjo8mOHBv+NxG83A/QysnwyXf4bIhWCIVuf5VFF7Ki9c3TYxmhLVKuUaB9CVBI+SapyScIt8ys3NjRMnTmR9Aw7OalXz5PsPS7/vSOm3EOKZJom3EEKIvMlsUntL1keqpciOHpkbj1sxw43f4ewcSLimznMPhrDB4B9um6TYlKQm3AC6Yur2XXwl4RYC1O+BS2FwdIf4i2rpt3c5dZg/Kf0WQjxjJPEWQgiRtyiKmmjrz6s9lmudH1ZTzcQQRXf2qz2Vx5xSp118ocwAKPZK5sb1To9Vwh0kCbcQT6J1AbcSauJ99zB43FHHr3fMQLtxIYQoICTxFkIIkXckR0PcRXU8YEUBXdGMt+EGNdE+PRPu7lente5QuicEv565cb3TY05Wq8yigC4Q3EPApYgk3KLASUhI4JVXXgHgl19+QafL5vdHo1EfTjkmgf6C+uDKq7z6PZLSbyHEM0ASbyGEEPZnjIO4yxB3SW0v7eoHWteMrx9/Ta1SfmOjOq1xVMfhDn3TNr2Jmw1qKbxifphwBz9MuCVhEAWT2Wxm8+bNltc2Yyn9vgt3D6kdEErptxDiGSCJtxBCCPsxJaul2/rzYIhV24O6+mV4dWclBofTP8DVlaAY1ZmBLaHsQLVjp+xKSbjNJtAFqCXcrn6ScIsCz8XFhWXLllle25RGoz64ckx8WPp9D7xS2n5L7REhRMEkibcQQojcZzZB4g2IjVSrnDp7q+P/ZvRHtzEBhwvf0TR+Cdr4eHWe7wsQNhS8y9sgPoMal9moVnd3LyUJt3imODo60r1795zdidZVLf1OSin9LgWeZcDRLWf3K4QQdiCJtxBCiNyjKJAYpZZwJ94Cre5hwp3BhNZshGu/wrl5aJPuoAUUz3Joyg2BIi9mPz6z8WEJd0rCHQKu/pJwC5FTNBp1eEBTojqCQfI98Ax72PZbSr+FEAWHJN5CZNH+/WrnTQcOHKBu3bp2jkaIfCD5PsRehIQrD8e7Dsx4D+OKAlE74MwstfM1QHEN5E+lK1Ve6IKTUzb/OzMb1TanJoOaaHuEgIs/OGSiJ3UhChCTycSff/4JQI0aNdBqc/i78Gjp971D6kMvKf0WQhQgmX6EHxcXlxNxCJHvjBs33upfIUQ6DHqIPgF39kH8ZbVtZ2aS7vtHYX8fODJcTbqdvKH8+xjrrOCqY8PslUabjWrJe8JNcPKBIi+oVdZ1gZJ055JHH2KKvCMxMZEXXniBF154gcTExNzZaUrpt4svxJ6Duwcg4Yb64E0IIfK5TP9aKVq0KG+++Sa7d+/OiXiEyBd27drFrl07ANi5c7t8H4RIiykRYs6pCXfsGXD0APfiaq/GGaE/D3++B/v7QvRxcHCB0m9Cg7UQ0g0cnLMem9moVnlPuAGO3uBbC3xrS8JtB/IQM2/SaDQEBwcTHByMJrerfGtdwb2keg+5exCi/wZjQu7GIIQQNpbpxHvZsmXcu3ePxo0bExYWxsSJE7l+/XpOxCZEnjVy5Bi02ucA0GorMXLkGDtHJEQeYjaqQ4Pd+UNNmDVa9Ud0RocLSoyCv8fB7q4QtVNdv3gHaLAGwgaBk0fWY1NMkHj7YcLtqSbcRWqDW5Ak3HYgDzHzLjc3Ny5evMjFixdxc7NDdW+NRu3QUEq/hRAFRKYT7/bt27NmzRquXbvGwIED+e677wgODqZNmzasWrUKo9GYE3EKkWfs2rWL7du3YDJ9AIDJ9AHbtm0usD8YDQaDvUMQ+YViVqts3z0Adw+DOVntOM3ZO2PrG2LhzFewswNcXQuYoWgjqPsjPPdxpoYZSx2bCRLvQNw19QGAb021Mza3Yhmv8i5sriA/xDSZIC4O7t6FpCR7R5OPaV3V+4gp/mHp9wkp/RZC5EtZbhjn5+fHe++9x/Hjx5k2bRqbN2+mU6dOBAUFMXLkSOJThncRooBRfyhWAVo/nNMGrbZygfrBmGLv3r34+fmzb98+e4ci8jJFedgh0p9wZ7/aiZpbkFpSlZH21+ZkuLAMdraH84vAnAQ+VaH2Qqg+We3oLMuxPZpwu0GRWg8T7uKScNtZQXmIaTZDfLyaYF+9CmfPwsGDsHMn7NoFe/fCzZv2jjKf02jUTg+dC6vNVu4eUB/ySem3ECIfyfKvjlu3brFkyRIWL17MpUuX6NSpE3369OHq1atMmjSJP/74g99//92WsQphdyk/FOFn/n1u5YDJNIpt2zqxe/du6tWrZ8cIbevjj0fy4EE0H388kq1bN9k7HJEXGWJAfxHir6hJrs4/422vFTNc3wBn56pjeoM6Xna5weDXIHtDCSlmdVgiY7z6Y927IugCwMEp69sUNmX9EHMjjz7EzIv3G7MZEhPVv4QE9e/BA4iJgeRkdb7ZDA4O4Oys/nl6wvXrBiD/fe4SExPp2rUrAD/88AOurq52jghwfDj8YNIdtfTbozR4hqql4kIIkcdlOvFetWoVixYt4n//+x8VK1Zk0KBB9OjRAx8fH8syderUoUKFCraMU4g8IeWHosnUHjA98k6HPP2DMSv+fcjwBtu2LS1wDxVENhkT1B7K9RfBlKD2VO6oy9i6iqJ2uHZmllp6BeDiB2UHQFCb7JVEK2a1xN2oB2dfKFwBXANAm42O2ITN5eWHmIqSOsGOiVGT7KQk9c9sVpd1dgYXF3B3h0KF4PERt44d28uQIa1ZunQ9wcEv5f7BZIPJZGLt2rWW13mGxkEt/TYmQMxpNQn3Kq/Ok3G/hRB5WKZ/3fTu3ZuuXbuyZ88eatWqleYyQUFBfPzxx9kOToi8JPUPxUd/iOSNH4y29O9DhkVotUcL1EMFkQ1mA8RfA30kGB6opcmuRTK+/oN/4PRMuHdQnXb0gNIRENw1e6VWihmSox8m3IWg8PPgGigJdx6VFx5iKoqaRCck/JtkpyTYiYlqKXZKvunkBK6u4OaWdoKdntmzRxIfH82UKSPp2DF/3T+dnZ2ZP3++5XWeYyn9vq3eT9xLSem3ECJPy3TifePGjaf2bqnT6Rg1alSWgxIiLxo5cgwajS+K4gJsAFLalm0CNIArGo1vgUhQrR8yaAvcQwWRBWaTOt61PlItYXL0ALeSGS9hir+qdpx28+F3Q+MEwZ2hdG9w9slebMn3wawHl8JQuMbDEu4MDlkmcl1uP8RUFDWJTi/BTkqyTrBdXNQE28cHHLNR+eLIkV0cPqzWGtq3L//VGnJycqJfv372DuPJNA7gWlRtUhJ7Wm1e4lVOLf0WQog8JtP/pXh6enLjxg38/a1vanfv3sXf3z9vVUcSwkZMJhP79+9DUeKBNg/n6oDvgU6A2sOqosAff+zFZDKhzWiRSB5kXRoFBbEqvcggRVETbf15tTMjrbPaE7gmg5/vpHsQuQCu/Ky2AUcDQS9D2bfUMbOzE1dy9MMJrZpw6wIl4c4HcvIhZkqCnZJkx8SofwkJaoKdMvCKk5NaTdzVFby9s5dgp2fuXKk1lGsc3UBbQh2K8O4BcE9p+y33AyFE3pHp/2qUdHqQTEpKyptVkYSwAa1Wy82bN4iNjbXMM5lMHDlyhFOnTlkl2Z6envk66c7LbS9FLkuOhriLamm1AuiKZrxzMmM8XFwOF5aqwwABFKkDYYPBKyzrMSmK2qGbIRo0Xg+3WxtcszG2t8g1tnqImdKZWUqSrddDdPS/JdgpoyA6Ov7bDtvLK2cS7LT8W9qdf2sNmc1mTp48CUCFChVwcMjyQDi5Q+OgdqBojIPYUw9Lv8Ok9FsIkWdk+L+gL7/8EgCNRsOCBQvw8Pj3R47JZGLnzp2UL1/e9hEKkUd4eXnh5eVlmTYYDBw5coTAwECcnPJfj7XpSV3anUJKvZ8ZxjiIuwxxl8CUqI6fndF2k2YjXF0D576G5LvqPK+KUG4I+KbdL0iGGWIh6T44eYB3FXAqCmyVUq18JLMPMc1mLfHx/ybYcXFqgh0f/2+CrShqQu3iov55eKgl2vb0b2l3+4dz8t/9MyEhgeeeU8dY1+v1uLu72zmiDHJ0B63uYen3QfAIBY9Scp8QQthdhhPv6dOnA2qJ99y5c63+c3R2diYkJIS5c+faPkIhRK5Ju7Q7hZR6F3imZLV0W39eTXJdCqtJd0YoCtzaAmdmq72dgzpWdtm3IaBJxsbzTo8xTh0nXOsG3hXUDpUc3f8t1hT5SnoPMT09AzEanSwl2FeuqIl2UpJawg3qUF0uLmoVcXd3tTQ7r7Eu7c7ftYaKFMlEx4l5yaOl3w/+edjzebmM38+EECIHZDjxvnDhAgCNGjVi1apVFCpUKMeCEkLYR+q2l48rOB3IiUeYTeo42rGRaoLr7K0mtxntOO3en3D6S3jwtzrtXAhC+0GJDtkbN9uYoP5g1rqAZxi4lwQnz6xvT9id0WhdRTw+Hu7dU9/bu1d9X1HUj56rq5pk+/ioCXZ+GSkqdWl3ivxV6u3u7s7t27ftHUb2OLqDuysk3lbbfnuEqmN/y2gHQgg7yHRrp23btuVEHEIIO0u77WVqBaUDOcHDAYuj1BLuxFtq9Uz3EhkvnY49p47FfXu3Oq3VQUgPKNVD/cGbVaZENeHWOKpVRN2Ds9/zuchVjybYiYn/VhGPi1NLr5OT1bGwHRz+LbX29laT7fySYKcl7dLuFPmz1Dvf02gfln7rH5Z+331Y+p1PS/OFEPlWhhLv9957j3HjxuHu7s577733xGWnTZtmk8CEELkrrbaX6cnvHcgJ1CG4Yi9CwpWH1TIDwSGDz2ITbsK5eXBtHaCoP2yLd4AyfcElGz9mzcmQeEd9rSsJHsFq6Xl+zsQKuLQS7AcP1KriKQl2Sgl2ShtsLy/135TLajbD9evW8/KruXOfwVpDhhgczszASakFBNk7mvQ5eoB7Stvv/eBZRh37W0q/hRC5JEO/so4cOYLhYVu6I0eOpLucJr//jynEM+7xtpeiADLo1U7T4i+ByfCw47QMdjpkiIHzi+DSj2qSDFC0CYQNUkuls8psUEu4FbP6AMC9FLj45v8srACxRYJd0JlMJv7+O6XWUEcgBCj18G8P8BeQf2oNJSYm0qdPHwAWLlyIq2s6HSye+i/aszNphg6HyO5QunvebRKi0ar3GKMeok+owx16lpXSbyFErshQ4v1o9XKpai6EEPmQKRHirkLcBfVHp4svuGawOrgpES7/BJGLwPiwRkShGlBuKPg8l/WYzEa153OTQR2qzL2U+iAgOx2xiWyRBDtjzGa4cweuXVP/rl+Ha9e0lCv3gGvXNNy754Ci/HtChgx5wP/9n94ynR9qDZlMJr777jsA5s+fn/6CvrVQvCrgFHMSLiyAKz9Cqe4Q3FUtZc6LUkq/E26B4T54lFGbtWSnTwohhHiKXBrRUgghhF2YjZBwXW3HnXRPbSvtXjJj6yomuLYezs1V24CD2jlRuSFQpG7WMy3FpMZiSgDXolCoFLj4g0PeTkTsISEhgbt37+Lr64tOp7PZdk2mfzs4kwQ7bbGx1om1mlyrfzdu/NvTurV/f1bpdBAUBIULQ4UK3hQr5p1rsduCs7OzZUQb5yd1Hx/UEqNbGY5s+ZpajivRxJ2Hs3Ph4vdQ6g0o2QUcbffZtRmNFtyC1FpA0X8/bPsdpj6UFEKIHJChxLtjx44Z3uCqVauyHIwQQggbUcxqsqy/oJbqOLlnvOM0RYHbe+DMTNBHqvNci0LZtyDoZfUHa1ZjSr6vDvHjUkQtLXcNyHjb8mfI7t27mTF9GqvXrLF0QtahfXuGvfc+devWzfB2UhLslFJsSbD/lZysJtCPJtQpr69fh5iYJ6+v1UJAgJpcFyv2778pfz4+6jm8cgWqV8+VQ7IpJycn3n333YwtrHHghmMdjC92wOn2Fjg3Xx1W8MwsuPgdlO4FJV4FbTrV1e3JyUN9MJAQ9bDn8zLgESKl30IIm8vQrx1v7/z1lFYIIZ5ZiqK2l467CPHXQeuklupkNLmN/lsdGuz+n+q0kxeU7g0lO2e8LXhaMRmiITlGHRu8cPmHnbnJD9u0zJkzh7fffpsKxbWU9tNw7paZ0n4OnDz4K/Xrr2H27NkMHDjQap3HE+z4+H97EU8ZB/vRBNvZueAn2GYz3L37b1L9eMl1VJR6Tp6kcGE1oX48qQ4KgqJFwVGeGVnTaCGoJQQ0hRsb4dzXkHANTk2HC0vVe0mJDuCQxzo002jBLRAMseqwiCnjfrsUtndkQogCJEP/ZSxatCin4xBCCJFdydEPE+6rakahK5rx5DbuEpyZDbe2qNMOzmobzdIRavKdFYoChgfqn5M3FKquPgTIagL/DNi9ezf/z955xzdd53/8mZ1075Yu2lJAQBD3AHGLG1Dup556TpQD9cRx56mncuqd64DzFBT3OfA8FdedKA4EREURHAfKKqMDSoGOtEma8f398W7adNK0SZu2n+fj8X00SdPm07RNvq/P+/1+vWbOnMkNp2ucf6SHE+8HuIzNu1/i87t8vLEaZsyYQU7OaMaMGTfgBbbd3rpaHSiw224Hb8JqbV2tDqxgR0X1zM8Rifh8Pnbs2AFAbm4uen0Q3gt6I2SdA4POgNL3YfOz4CyDDY9A0T+h4CrIPi/yNt9MsRKL6CyHvVUN1e/BkbdOhULRJ1F7tQqFQtHXcduhdkeDU3m9OPR2tqXTVQGbn4HixTJ7jU5OmAuvk+zbLq+pRua4TbEQPwaisiJzzjPCmDd3DiOyDcy91MMpf9Fj0B+E1/c8Bv233PvWL3z8Rx8f/8/AXx6Yy22/H9fvBbbb3dQOXlzcvBW8tFTa5jvCYJDKtF9It6xcJ6q0unZxOBzk5+cDYLfbiY7upBljIHojZE+GzLOh+B3Y8pyMwKz/KxS9CEOuls9F0riJ3tgw+10DVT9AfQXEDlPVb4VC0W269Er3xhtv8Prrr7Njxw7qW2wnf/fddyFZmEKhUCgOQCun8iSwpnXuaz21UPQybHtZTM4AUo+HYTMl37areOxiUmSIhoRREJUNxi6csA8ANE0qsk6nHJWVDt5+5x0evdjHFxth2QYfcB9gwOu7j8/WT2XVJrj2JA+3vrqY1FQHVmvf3szQNHEH37Ahie+/17UyMetMO3hiYvsV64wM1Q7eHaJCVfLXmyB3KmSdK5t8W58X08ef7pPLQ6ZJi3pX/SPCQWP1e7d0E8XkQ3Se6thRKBRdJui3o8cee4w777yTK664gnfeeYcrr7ySLVu28M033zBz5sxwrFGhUCgUgfjcctJas0VOCINxKve5YedbsOUZMToDiD9YnMqTDu/6mjx1DYLbCrHDZT2RmuXbw/h8TeLaf1RXS7XW3x7udkNlZTVer48h6XD3G/5q9+SG7zIFg34Ed7/xCzed4cPr81FbW90nhLfd3lxMB7aFl5WBy2UCjm/36y2W1vPVmZmQna3awcNJdHQ0tbW1of2mBouMsGRPhh1vSNW7rhh+vEcEeOG1Mh8eKZGCeqN067gbcr8duyT325YROWtUKBR9hqCF9/z581m4cCEXX3wxL7zwAr///e8pKCjg7rvvZt++feFYo0KhUCgAfN4Gp/Kt4NojleTo3M71ymo+2PUxbJovJ7oAUblS4U4/uev9tl4nOCvkBDWmAKIHg3lgGnK63c3FdV2dCOyaGhHXLpeIcJ0OTCZpD7daIT5eqrJpaXEY9Ho++tEXUO32n9zrG6veB2eDQa8nOrqLs/chxu2GXbvadgYvKTlwO7her5Gc7CA310pWlr5V5TopSbWD9zsMVsi/FHLOhx2vi/Fa7Tb4/g7Y8qyMuqSfGDni1hQDxijZXNz7jXTyxA6RTU+FQqHoJEEL7x07dnDccccBYLPZqKmpAeCyyy7jmGOO4fHHHw/tChUKhWKgo2kitO1FUnExmKUK09m2zL3fwC//gOr1ct2cDIXTpOrU1dlKr0tOQnU6EfAxgwfEDKSmiYAOFNh2uwhsh6O5wZleL+LabIaYGBGQhg5+ZVarjRNOnMRzy97FoB8eUO32I1XvZ5dt5MSTJvdYtVvTmtzB26pcl5fLhkJHJCS07QyelQVpaR7Ky5eSmXlWcAZeir6PMUoMHHOnwrbXZPTFvgXW/V7mqodOlxGYSNh50enBmgq+etm8dO1p2mxU7ecKhaITBH3GlZGRwb59+xg8eDC5ubl89dVXHHLIIRQVFaEdaBBLoVAoFMHh2gf27eAolpPPYJzKqzdKjm7FKrluiIL830Der+WEtyv43GLIpvkkEiw6HyzJkXFiHEK83ubi2uGQynV1dZO49njkvgaDiGuLRQSm2dz1p+OII07h008X07za7Ueq3nX1UzniiJO7/sO1QW1t++3gpaXyM3eEvx28rUzrzEzoyJfrQKJd0Tu4XC6uv/56AB5//HEsljCKS2MMFF4Dgy+Eba/AtkVQsxG+uxniR0LhdEg5NjJeZ/RmiM4W87XKn8BRptrPFQpFpwhaeJ988sm8++67HHrooVx55ZXMmjWLN954g2+//Zbzzz8/HGtUKBSKgYe7BuzbwLETvO7gnMrrSmHzAihdAmigM0LOBeIg3NWqtM8jgtvnkRPM6Dyp/vTxE81AczN/e3hVlQhRf3u4f0/ZZBKBGdgeHmo++WQxkAxYgA/auIcVSOaTTxbzq1/N6PT39Xjabgf3HwduB4e0tPajt5L7397LgMfj8fDMM88AMG/evPAKbz+mWKlyD75IzB93vAZV62HNjZAwRj6XdGRk/LGZYmXcp7H9PKeh/XxgjtooFIoDE/Rpw8KFC/E1bE/PnDmT5ORkVq1axXnnncd1110X8gUqFArFgMLjgLodIrq9dVJNtnbSFby+UgyKtr8Omltuyzgdhs2QmcSuoHml6u51imN6TD5Y0kAfQe7DB0DTWpub+avXTqeIa3fD0xUYzxUbK4Kyp7qfvV4vP/30JVAHnNPhfX/8cRVerxdDQ++6vx3c7wreMnpr9+4DV5bj41sbmPmvZ2TIxoNi4GAymbj//vsbL/co5gQYfr105xS9KEZslT/ANzMg8TAY+ltIOrRn19QWzdrPdwa0n+eq9nOFQtGKoIW3Xq9vNoN10UUXcdFFF4V0UQqFQjHg8NaLU7l9C7irwJwoVe5Ofa0Ttr8GW1+QOC+QqtDwG6RNsytoPqjfB+5aObFMGA3W9MjK222Bx9O6PdxvbuZvD/d65b5GY1N7eHS0iMreLqIZDAY+/LCMurqaxttcLgd1dXaiomLw+aLYtcvArl1G9u2LZs4cQzNx7XR2/P0tliZB3da8dUxMmH9ARZ/CbDZz55139u4iLElw0CzIu0w2FXe+Bfu/g9XTIPkoaUFPHNO7a4QW7ec/ymt53DB5zezjXUEKhSJ0BH0GtXz58g4/P2HChC4vRqFQKAYcPi84yxqiwfaCKU7MyjqjAn0eKH0fNi0EV7ncFjsMht0AKcd0TUlqGrgrob5aqu3JI2SWu7Nz5WHG5xMR7XJJOzjAzz/LZX97uN/czO8ebrFI5FRCQmRnOns8UFkZR2lpXKOYDqxcV1Z2/PU6XVM7eMt56+xsMXdT3mWKPok1BUbeBgW/gS3PQfE7sHe1HCnHSQt6VzcZQ0lj+3kFVKyW1/LYAtV+rlAogC4I7xNPPLHVbbqAkzuvv5ygUCgUivbRfODcI9Fgzt0yvx2V3Tmnck2DPcth4xPy9QDWQTDstzDojK5VWDRNKu31VXKSmHSYCO5eaJcMFNf+o65OKtd2e1PutccjYnPrVpm7NpshLk4+RqLA1DTYt6/5fHXLdvADvYXGxzcX1IF51hkZ8rMrwo/PJ78rj6fpY+DlwLZ+na73uym6gqZpVFRUAJCSktLsXK/XsKbDqD9C/uWw9VkoeV/MIytWQdoJEkMWN6x316jTy1iO1yVjQ65yiBkC0Tmq/VyhGOAELbz379/f7Lrb7Wbt2rX86U9/4oEHHgjZwhQKhaJfomnSwm3fBo4SEdq2QZ1v4d7/PWz8B+xfJ9dN8TDkKsj9lbQ7dgV3Nbj2S7U9YYxElRnDG1UVjLgGES7+aK6oqCZxXVoqojNShHZdXdvCurPt4GZz61bwwMuqHTx8BIrnlqLa620y2QP5ezQa5TAY5KPNJhtA/sNolI4Lo1E2TPoadXV1pKWlAWC324nuyJq+p4nKhIP/BPlXwJZnoPQDKP9cjvRToPBaMTrrTQyWhvbzaplPd5ZBbKFqP1coBjBBC+/4Nt49TjvtNMxmMzfffDNr1qwJycIUCoWi31FfBbXbxYRH84IlpfMVEPs2iQYrXybX9RYxHsq/HExdVGMeuxinGaIgYZRU3I2hO7luKa4DY7lqa5tMzToS1x21hvdGDJXHI5XptkR1SQm02JtuRWA7eFuz1j1p5tbfaa8q7b/e8u/HL6D9H/0O9lariGq/iG7vYyQUhAcc0TkwZjYUXAmbF8KupbD7E9j9KQw6HYZMg5i83l2jKU7i0lT7uUIx4AnZtFt6ejq//PJLqL6dQqFQ9B88dVC7Q0S31yGCu7MVZeceOaEseVfEOnrIPk8qOta0rq/HWSFriB0uJ6+m2C59q3CL655G00Q8t+UMXloqkVwHagePi2s/z3rQINUO3lU0re1KdGCVur2qtF9QR0U1iWmLpWMhbeg7xv1hITo6Gi3wCY1kYvJg7F+g5ip5vdz9KZR9CGVLIfNMKJzW9WSHUNCs/Xx7QPt5LhjUC4JCMVAI+nTnhx9+aHZd0zTKysp48MEHGTt2bKjWpVAoFH0frwvqisFeJO2GluTOO5W77VD0T9j2CvhcclvaCTBspsTVdGk9ThHcBpO0YUYP7lTVpb+Ja4ej9Xy1X2SXlsrnO8Jkai2oA6/Hdm0PY0CiaU1Rbna7/K11VJUOrEgbDM1bu61W+d20J6RVVXoAEFsIhz4M1T+LAC9fDqX/gbIlkHUuDLlaRnt6C4NFNjpbtZ9nqD9OhWIAEPSp0NixY9HpdK12QY855hiee+65kC1MoVAo+iw+DzjKxPjMtVfEbXRnncrrYcebMrforpLbEsbA8BshcWzX1uN1SZujTt/Q5pgncWWBD9uPxLW/Hbw9E7N9+zr+ep0OUlPbdgbPzISUFNUOfiA0rUlA+/9uAgW1H52uqbLs9crfUHR0k5A2mzsW0gO9Kq1oh7iD4LA5UPU/2PSUmK8Vvy1mbNmTYciVMmvdW5jimtzP934DthyIGyK3KxSKfkvQp0lFRUXNruv1elJTU7FarSFblEKhUPRJNJ84lNuLwFkurdzROZ0z0tF8UPYRbFogpmsA0Xkw7HqpdHelGuLzgGuPqCBbFj7bYFwk46rT4drfd8W1pkm01s6dOv73vywcDn1jtbqkpHPt4LGxbWdZZ2WpdvCOCKxItzxaCurANm+LReLcbLameWm/qNbpYMUKOO44+Zwq/EUGLpeLP/zhDwA89NBDWCx90JE7fhQc8ZiYUm5+SuLHdr4hozs554s5W2e7kEKNziDiP7D9PLYQonJU+7lC0U8J+hRq8ODB4ViHQqFQ9F00TSrbtUVQVyoO5cE4lVd8JU7l1Q0+GZYUicXJOrfz36MBtxvqXRqumkrqnR5c+kwc+sHUuBKprdP3GXHtdLbvDF5S4m8HNwJHtPn1JpMI6LacwTMzZQ5b0URHgtrna5qdbk9QR0U1Ceq2jo7+pvyt5n4RrogMPB4Pf//73wF44IEH+qbw9pN4CBw5H/atkQr4/u9g+2uwc7EkQhRc3qoLqMfwt5/XV8kGgSPQ/Vz9QygU/YmgTq88Hg9z585l0aJFbNy4EbPZzLBhw7jyyiu59tprIyPjUaFQKHqS+kqo3Saz3JoGtrTOx3pV/QwbH5MqDEjrYf7lMPjids3XPB6or9fhqtc3fNThcumx1+qprdXhstfidrmoJwOfZRCYEtAZDBEnrj0eKC9vvx18794Df4+0NI3k5H3k5SWSna1vJqxTU1U7OLQtqP0bLy2zpgMFtb8y7Y/IaktMm82q1bs/YzKZuOOOOxov9wuSDoejGirfm56Eqh9h28uw800YfBHkXQLmhN5ZmzleEipcFbK+6Fzx81Dt5wpFv6HTp14Oh4PTTjuNL7/8klNPPZUJEyYAsGHDBmbMmMF7773Hu+++S1FREStWrOCKK64I15oVCoWi93Hbxam8boe0ClpTwNDJkZu6YmkpL/tQruuMUnUZcjVeQwIul476Wr18dIuwrq3VU2PX43LrcNfrcXvA49Gh04FOp2GkDrOuGpM1GmtKAaboFAy9eLKsaVBV1dy0zC+wO9sOHhPTer46sB3cZPJQWrqSzMyz0A8wle0X1C3np9sS1IEz0TYbJCW1FtT+tm//oQS1wmw288ADD/T2MkKPTgcpR0PyUTL7vekpqF4PW5+H7a9LTGPer7uc9NC9tfnbz51QUwSOcjHCVO3nCkW/oNPC+8EHH2Tnzp2sXbuWMWPGNPvc999/z3nnncesWbN48803G2eCFAqFot/hdUJtsbSVu2vAmgzW1M59bf1+tM3Pws430GnS612bcBYViddT5cnFvtaAs16Hu16H26PD45EuIp1Ow2gAk0nDZNKIjfFiNMlteB3Somiwgi1PKu6dzQbvJk5nk6huGb1VUgJ1dR1/fWA7eFvxWwdqB++NHO9wE1ihbimqfb6mztOWFWp/q3fgDHVbhxLUCkUDOh2kjoOU42DPchHgNRthy9PShp5/iVTBjTE9vzaDFWJyVfu5QtHP6LTwfu2115gzZ04r0Q1wyCGH8Oijj3LhhRdy5ZVXcsMNN4R0kQqFQtHr+NzgKIWarVC/X9oRY1p7Xvh80goe2A5e73QQtftlkqufx6jVArCH8fzkvZWqfaPQ7QODQUS1yagRHeXDZNI6bgf3ucBRKdFg0bkyU26MCumP7PXCnj1ti+qSks61g6emtm1i5m8HHyhCMBiX78AKdVRU02GxKEGt6Dk0TaOuYfcsKiqq/44T6nRiYJl6POz+TEzY7FulFX3bIsi/DHIvbHf8J6z428+de8T9PDpH8r97oxqvUCi6TaeF9/bt2znqqKPa/fwxxxyDTqfj2WefDcnCFAqFIiLweRucyreCsxzNGEO9MZd6lwFXjY76ej2ueh0Op44auwGHQ0+9WyrWXreXXP7NQbp/YNXtAaBaN4rtUTdTaz2WOBPE4Q5uPZoHXPvlsjUDojO7PAPobwdv2QYe6A7uN2Frj+jotp3B/e3gfdmPqTNomgjntlq+A5+7tkzJWrZ8t2z3VoJa0ZvU1dUREyPVXrvdTnR0dC+vKMzo9JBxCqSfCGVLJQe8bgdsfBy2vSoGbDkXdH6kKGTrMoAtQ7qt7Nua2s+jc0HfT2bvFYoBQqeFd1xcHOXl5eTk5LT5+V27dpGUlBSyhSkUCkVvoGkBzuDVFdTv34mrugKnx0KNaxi1DhNut456jw6PG3w+mbPW68Hc0ApuNfsYbFpKLnOxeSWC0WXIpiTmd+y3ngk6PUGfLmlecFeC1yPt7bZsqbofoArldEJZWdsGZiUlEiPWEUZj89nqttzB+2shrD2Xb4+nyeUbmleoTSaIj287NkuZkikUfQCdATLPgIxTxYdjy9Piy/HzXCh6CQquhJwpnTfRDBUGa4P7eSVUfg+OXQ3t52n990VYoehndFp4n3TSSfzlL3/hzTffbPPzDz74ICeddFLIFqZQKBThwC+s/fPHu3dLxdLpBLtdDnddDfXVu3Hb94nAMg9GbzBgMmqYzXLEREs7eMvznej6NWTX/I0Y9zoA3LpEymKmUxF1IZquCydqmg881eBxitCOzQZzEuhFufnbwduL3aqoOPBD+NvBA03MAt3B+5tI7Iyg1unk5w6sUsfENAlqv0t8S0Hd227xCkWoiIqKwm63N14ecOiNkHU2DJoIpe/D5mfBWQYbHoGif0LBVZB9Xs9Xnc0J0mru3AN7v25wP1ft5wpFX6DTpwj33HMPRx99NMcccww333wzBx10EJqmsWHDBubOncv69ev56quvwrlWhULRwzgcDqqrq4mLi8Nm64X5ti4gM9bND5dLcp9ra0Vwu91yO8C338pHnQ5M+jrMnl2YfLuJMrsx5cShN1oAX8PRPlbPZrJq5pLg+gwAr85GedTl7Iq+Cp++i+Y87ho0t51qZyKlVYWUlCdSUmZsJqzLyoJrBw8U1dnZkJEhrc79Aa+3/eisQEGt1zcX1IEV6o4EtSoqKQYSOp0uiPbyhn8O526wJfZ8O3Y40RshezJkng3F78CW5+TnXP9XKHoRhlwtn9P34K5by/Zz5x4R39E5qv1coYhgOv0qMXLkSJYuXcrVV1/NRRdd1GiyoWkaBx10EB9++CGjRo0K20IVCkXPsXLlSubNncPb77yD1+vDYNAzedIkZt18C+PGjevVtUmOdZOg9l/2i2qHQ8SW//Cj1zcXUxYL7NsnIlTvc8qJlKMU9E4xtDEkdGo9Ju8uMu2Pk+x4Gx0+NAxU2C6gNGYmHkPn3M5d9TrKdpkoLjNRWmamtAxKSvSUlOdSsstGbW3HUVlGY3N38JbxW/HxfV80+nxNv1O/oPZvnpSUyMeWgjqwQm2xtC+oB1gSmUIReixp8tGcAu59ModsigZTfM8K0jDgcDiprqklLjYaW+5UyDoXihdL/JijFH66Ty4PmSYt6roebBFq1n6+Dpy7RICr9nOFIiIJ6tXwmGOO4X//+x/r1q1j48aNAAwdOpRDDz00LItTKBQ9z4IFC5g5cyYjsg08erGPIemwZbePpz9/j+OPf5v58+czffr0sDy2vw08UFD7BXZtrRwuV5MAC3SD9s/XGo1SwY2L67hK2RhF5dglUS0eu7TqmTM6tVaDr5qM2mdIq30JPS4A9ltOoyT2JlzG/Gb39Xphz14jpbtMlJSa5eMuEyVlZkrLTOzZe+AKRUpK6/lq/+X+0A7uF9OBR8tKdaBojo0VQb11Kxx6aNuZ1EpQKxRdp76+ntmzZwPS9Wg2dzAq48+YTjoMcICrQuainbtAA8xxEsul6zv/lCu/Wse8Ba/w9gefN21An3kCs2ZcwrijL5Iq+I43pOpdVww/3iMCvPBamQ/vyZ+1Wfv56oD2816IQlMoFO3SpW3IsWPHMnbs2BAvRaFQ9DYrV65k5syZ3HC6xtxLPc2Ey40TPdz0EsyYMYPRo0d3qfLt9bZuA6+vb2oDr61tLrwCRZdfWJvNIrL8Vc0u4fOAs1wuV2+UkxNrRqcqBDrNRWrdIgbZn8KoVQFQYzqM9fyRTXsOp+QHEyVlJkp3NQjsUhNl5Sbc7o5PwqJtHrIGOckcpJGZYyErx9zMHbwvt4O3Va3uaOMkKkra46OjpVLtr1YHtoHrdPI9tm6VTQiT6q5UKEKK2+3mL3/5CwB33HFHx8Lbj04nVW5zPETnSfSis1w2N+tKpPptig959GGoWfDcG8z8/YOMyGqxAb1sOcef/RnzH7md6VdOhfxLIed82PG6GK/VboPv74Atz0LhdeKQ3lMCvFn7uaRwqPZzhSKy6Nv9PwqFIqTMmzuHEdmGVqIbpHo47zL4ZIOBeXPntim8/e2/LQ+7XUS109k8dskvrPX6JkFlNovgCkvF0ueF+n3SHuhsCKG2pnbqpMTl8uHYsYraomV8tTuereV3sbniYDZWHM7O3UnYazsuORsMGoPS3WRm1JM1yC1HhpPMlH1kpdmJT01EF5XZKafySCPYanVMjPyOo6KaC2r/oQzKFIrex2g08rvf/a7xctDoDWBNkSN2CLj2igB37ZHDEC0CPcJE4cqv1jHz9w9yw+kw91Jviw1or2xA3/Ygo0cWMu7osbKJUHAF5E6Fba/BtpfBvgXW/R5ih8HQ6ZIR3lOv6warVLwD289jC8GS2ufeWxSK/oY6vVEoFIAYqb39zjs8erGvXcGr18O0EzzcumgxW7c60OttOJ1tV6u9XhFegXO3JpOILX9ls8fOATSfZF87GwS3wSiRXLU1jdUIn6+hHbxMWsClFdw/c61RvjcaGAVMa/dhkpM8ZGXUk9kgrJtEdj2pKR6Mfm0e6FRuSQLbcLAkR2Qbps/XXFi3NCwL7EZoq1rdlrAO1e/d6XQ2fjSpkrdCEVIsFgvz5s0LzTczWCAqUw53jYjwumJpjcYnbeim2J6dj26HeQteYUSWoZXohoAN6PUG5i14VYS3H2MMFF4Dgy+Eba/AtkVQsxG+uxniR0LhdEg5tufe+MwJsiZXBVR8DdGDIaZAtZ8rFL2IEt4KhQKPB3bvrsbrlZa6jihIA6/Xx/Ll1SQk2FpVM7vdBh5KNE12/R27wFVOtd1M6b4sistslJQZ2bQzjsqKFEp3mSnbfeB28BhrDdnpNaRnRZE5yNtQtRZhnZnhxmrVOvx6NE1myT12MMVBfD5YUnrVfCjQ/ftAbf4mEyQk9H612m/+9+FHH/Hyy6+QmTmIiaefHhHmfwqF4gCYYuXwV2Vde6QNva5MXnDM8VIN74XqrMPh5O0PPj/wBvSJXm5dtAyHw4nN1mIOyBQrVe7BF0HRy7DjNahaD2tuhIQx8rmkI3vm59MbA9rPt4iJaEwhRGdHXKeBQjEQiIRTY4VCESbaElT+w+8A7ncBr62Nw6DXs2V3x7FZW8vBoNczdGhcxM0d19dLzFZpKZTscFC6w0FJiY+SXdmU7h5Kjb3jlzyDQSMjzU12ejXDU77hoKTlFKRtZXBaMbGDD6d+0MX4DAlAVfCL89SBu1raEmOHgjW9yZAoTPjN6tqqVvsxGJo7vSclSSu41dpaVEeCYVmg+d/9U+XE8f6pPhZ+En7zP4VCEUJ0eun4sSRBdL6MATl3gWO3dCYZbTIPbrD02JKqa2qD2oCurqltLbz9mBNg+PWQ92sxYNvxBlT+AN/MgMTDGgT4YSH/GdqkzfbzIar9XKHoYbokvCsrK1m9ejXl5eX4fM1P0n/zm9+EZGEKhaJ9/CZlbQlqh6N5rFZgprEWUJA1GJpHLyUl2ZgwYRILl73HjRNbz3iDtB0vXGbkxJMmYbX2fK63zwcVFRIfFZhl7f+4Z0/gz2hrOJqTlOAha1A9gzLqiUsuZ/jgaHIGecgc5CYzaRc5zgWk1r2ODg8aOvZZz6M0djZOQ1bXFu11ysmOwQoxeWLiZgzdc+f1Nv3uA/8moHW1Oj6+qRU8UFD7W8IjokuhA1qa/3n1Jv4LzDgNbjil++Z/CoWiidraWmJipC3ZbrcHkendBQxmqczaMiC2tmEevFQ++uobWtHjwt4dFBcbjcHQyQ1og5642E48J5YkOGgW5F0mruc734L938HqayH5KGlBTxwTop/gAAS2n+/dC1GDISYf6LnNDYViIBP0K9h7773HJZdcgt1uJy4urjHPG0Cn0ynhrVB0g/ZElNstxmR+QV1f37ag1ulaZxlHRTVdPlC18pJLb2batLeZ9TLMvbT5/X0+uOkl+LnEyy33zgrbc1BT01xY+0V1SQmUlTVlN7eHzeolK8NB5iAPWYN8jW3gWZn1ZKa7sdnkyfJpXkrtW8iMGYJRc5Je9wLp+5/HoNUBUGU+npLYm3GYhnftB9HcMleu00NUFtgGSQtiF2j591Bf3xSHFmhMFxUlMVsxMU1u4IFz1r1dre4uLc3/AkzRO2X+p1Ao+gDGaDmicsBdBc4KcJTIyJCOBlf0mLBUam02K5PPPIGnly3nxomtZ7xBXnufXmZgylkntF/tbgtrCoy8DQp+A1ueg+J3JPpr72pIOU4q4PEjQ/fDtIe//dzjAPsmaT+35R/46xQKRbcJWnjfcsstXHXVVfzlL38hKiqy4yAUikghUFC3FFFOZ1PLt8vV+Qp1MIK6s4wdO54//GE+Dz00g6X/M3DtiR4K0mR3f+EyIz+XePnDH+YzdmzXRU19vQjoQEEdWLmuru746w0GyMhoyrLOzHCTlVpFVvIuslIrSUi2ojN1rjKj0zyk1r1GVu2TmHzicl5rGk1xzM3YLUd37QfUPFLh1nwyvx2VJSeKHZwk+nxNfxP+j4G//8B8ar+wjopqLq4tlrYr1m63u18YjwVr/udwOLDZer4rQ6HoL0RFRVFeXt54ucfR6aRCa06QbqH6fQ1t6LugbifozfI5Q2hnnm767SVMOOezDjegN5R4Wbjw1117AGs6jPoj5F8OW5+FkvehYpUcaRMkhiyuixu+wWC0gSEX3JWw/3vAICLcmBmRRp8KRX8gaOFdUlLCjTfeqES3YsDjd1SurHRitZpaCetAQR0oploKar2+yRE6XII6GKZOnU5h4WgWLZrLra8uxuvzYdDrOfGkSdxy76wDim6fTzrY2msHLy9v/vO3RVKSiGq/uPbnWWdmQnp6g8D0uhtMeYrFrMwYC8akzlVBNI1E54eMcPyNGK0MAKchl5LYm6i0TOxaJUXzyQy31ykO5bZMaTFsOIHxeJri1VrmWOt0TVXpqKimuC2rtXXlOpi/iVWrVnHWWWfzwQf/5dhjjw3+Z4ogqquDM/+rrq5Wwluh6AY6nY7U1NTeXoagN4I1TQ5PIdTvhbpS+ejYDaZoMCWEpBV9/DFjmf/I7cy47UE+/p+BaSd6Gzegn15mYEOJl/mP3N7c0bwrRGXCwX+Cgith89NQ+gGUL5cj/WQR4LFDuv3zdIhOB+ZEIBooh71rwFUiGezWVCXAFYoQE/Qr1MSJE/n2228pKCgIx3oUil5H0zo2JVu1aiUvvDCH1V9/xMuvvEJB/iAOOeR0zjn3Fg46qEmUthWj1ZuCOhjGjh3H2LHjcDod1NZWEx0d12ym225vLqZbtoYfsB3c1lCtzoTs7OYiOzNTnqt28bnBsVdccP1mZdaMTovlGNdqsu1/I9r9IwBufRJlMTPZY5sKui5Uhhucyn31dty6BNymIdR7k6ivNDbbZPH/HZjNkJjYftU6lMXpO++8m6qqSu68824+/XRp6L5xLxAXF9dq9vLrzcAhsHoLjGs4P22cvYyL652FKhSK8GK0gTEbbFngqWlqRXfulhdcv2t6N0Tj9CunMnpkIfMWvMqti5bh9fowGPRMOesEFi78dfdFdyBR2TBmtgjwLU9D2Uew+1PY/RkMOh2GTJOKfzjxb1hYU2VD27lb3ldj8qRzSwlwhSIkBC28zz77bG677TbWr1/P6NGjW7UwnnfeeZ3+Xl6vl3vvvZeXX36ZXbt2kZmZyRVXXMFdd93VODt+xRVX8OKLLzb7uokTJ7JkyZJgl64Y4LRs9w50ea6vb6pOO53N2739edQAS5YsYOHCmRyUaeD+XzU4Kv/Kx1Mfv8cdd7zNH/4wn6lT+76jstvtbwe3UVJia1W5rjqAqbe/HdwvpP2i2i+yExO7UFT2eRuqHCXSym20SvWjkycEVvdGsu1ziHctB8Crs7HJeB61CbPA0DmR5vGCu15HvVuH262n3uHA46xFZ4pCZ83BFJuM2WDGYoaUNmat/UdPbLysWLGCZcs+AS7js89eYuXKlYwfPz78DxwmbDYbkydN4unPm8z/7lusZ8Yh8nHJrQ2zl58bmTJ5kqp2KxTdpL6+nkceeQSA2267DbM5vCkMQaPTieGaKU4yquv3g7McHGXyPqE3yueMXTOFG3f0WMYdPRaHw0l1TS1xsdHBzXQHS0weHPJAQwV8oYjvsg+hbClkngmF00SkhxO9CcyDxNDO2dDWbxskFXBLinJAVyi6SdDCe9q0aQD8+c9/bvU5nU6H1+ttdXt7PPTQQyxYsIAXX3yRUaNG8e2333LllVcSHx/PjTfe2Hi/M844g+eff77xusWi3BcVQntxSYEO334xXV8vItovqAMN+f3uz4EVaptNLhsM8vl161aycGHHjsoPPTSDwsLR3ZqB7gk0TdrBi4tbG5j53cF9HZu6kpjYdit4VlZAO3hIFusD174Gh9t9YDA1tMAZOvXlJm8pmTWPk+x8Bx0aGkb2RP2Kkqhr2eGoIlMfjV8Hy9+TX1g3ffRp4uljMGiYTRomvYt48z5ikg1EJw/CkpiJOcrWrGrd2+cnd989G4NhDF7v8xgM67j77tl9vup906ybmTBBzP/OPxJW/OJjBrD8Zx/LN8Abq2FDsZeFi8Jn/qdQDBTcbjd33XUXADfddFPkCe9A9AYxL7OmSHt2/T7JBXftkYq4MUrywfXB/ww2mzW8grslsYVw6MNQ/Qtsfkpaz0v/A2VLIOscGHKNiOFwojdLK7yvXkztHGXSYRA9WEapevsNTqHoowR9atwyPqw7rFq1ikmTJnH22WcDkJeXx6JFi1i9enWz+1ksFjIyMkL2uIrIJzBvuGWV2uVqmp9uaUYWmE8MrQ3J/JFJBoMcwfDqq3M4KKtjR+WP1xtYtGhuRAhvu719A7PSUnnuOsJqbS6qA4X1AdvBQ4GmSWXbUSrRJzo9WJNB17mXLYOvkgz706TVvYIe6X3fZ51IcdTvqNHyqXf4gCp2lRvxepq+p8msYTZqmC0+EhN8xET7sNl8WMwaZoMTC3uwWHQYYnOkQmGKvJbmpmr3m4ABr/cePvtsap+veo8fP5758+czY8YMnlmmR284CAC9bjhnPvIjjnof8+fPV47mCkUIMBqNXHPNNY2X+wwGiwhT2yBw25s6pVx7wecJaEUP8iSgp4kbDofNgar1sOlJMV8rfgdK/gPZk2DIVWLUFk78AtzrkvdiR6kI8JjBYO6kp4pCoWikV19JjzvuOBYuXMjGjRsZNmwY33//PStXrmTOnDnN7rds2TLS0tJITEzk5JNP5v777yc5ObnN7+lyuXAFKIrqBotkt9uN2x9uG4H41xbJa+wuPl+TOG5ZofZ4mirTTmdzI7LAVm+Q1/mWgtrv6OyvTnd2PZ3F6XSy+uuPuP9XJrx6E17A3ZAR7f+IHq47Fe769xLq6mqwWsO7Q+52w65dUFqqo6RE1yCodQ3iWkdVVcdPhF6vkZ4OmZlag5jWyMrSGtrDNZIO8J4awj241tRXyy67q0KuW+KbBLfWcVeNTnOSVvsqmXXPYtTk/7+Co/if71b2145BV6eJS7jZC3rIynQRG+0SYW1uENhmDZNJa/r5fR45edO8YM3EF5OLz5wkn4vA/9n77/8LMTFH4vWeDbiBczAYjuD++//Ce++909vL6xZXX301mqZxyy23YLVKNc5ivQuH4zKeeOJvXH311f36dbQ/MhDe//oier2e+fPnN17v6PcTub9DC5gzwZQh0WSuCqmEO8ukjckYL9XwSBaQ0QfB2HnoKn9Av3Uh+n2rYeebaMXv4suegi/vCmkD7wZuj6/Zx9aYwJwh5qH2nVBbApZMiMkRU7tIfv76KZH7PzfwCOZ3oNO0A/kLt+bzzz/n0UcfZcOGDQCMHDmS2267jeOPPz6o7+Pz+bjjjjt4+OGHMRgMeL1eHnjgAf74xz823ue1114jKiqK/Px8tmzZwh133EFMTAxffvklhjZKlvfeey+zZ89udfurr76qnNgVfQpNg8pKC7t3R7F7dzS7dkVRXh7VeH3vXhs+X8dvdnFxLtLT60hPr2342HQ5JcWB0Rj0v3/konnJ9SzjIPer2DSJBqvSDWa9+TeUGw5TJwYKhUKh6PMke//HQfWvkuL7HwBezBQZz2CT+XzqdQm9uziFYgBSV1fHr3/9a6qqqg5o7Bq08H755Ze58sorOf/88xvb+b744gsWL17MCy+8wK9/3flcw9dee43bbruNRx55hFGjRrFu3Tpuuukm5syZw+WXX97m12zdupUhQ4bw8ccfc8opp7T6fFsV75ycHCoqKiLa5dbtdrN06VJOO+20Xs/c9c9NB1anAy/756X9MVn+qrT/ox+/zvFXpf1V6sBqdV/B6XRy1pmDuP9XPmacJre5sbE0+jlOq70KEw4A5i+Fu/6t578flHWq4l1b628B1zWrVssBLlfHYtFi0Rrav7VWletBgySSqk/gcTQYuewGb73M4hnEy6HJ0Ewvc9f1usYOCINRw2zyMUi3jELPHKK8WwDwmjJw5ExHl3UGZktzJ7Mvv/mRBc++zicr1/D0088wbdo1nDL+cGZc838cc8RouZOmSXXEUwOmJIjNB0u6zBFGOOeccx6rVu3F610BBP7sPgyG8Ywbl9qnq95ffvklZ5xxBvAyNtsZPPfcUq666jQcjg+Ay1iyZEmfj04baETS+19/xul0kp2dzQsvvMA555wT0u/dZ3+HHkdDPnipfPS5xYzNGBuSaLKwoWno9n+DfstT6KskoUMz2PDl/B++3Esk3zwI3B4fS7/ZxWlHZmAyBuH+6XWK94reIC3oUdlBP7aia/TZ/7l+SHV1NSkpKZ0S3kG/qjzwwAM8/PDDzJrVZF5z4403MmfOHO67776ghPdtt93G7bffzkUXXQTA6NGj2b59O3/961/bFd4FBQWkpKSwefPmNoW3xWJp03zNZDL1iT/McK0zUEy3ZUTWcm460ISsZau3PybLL6D9bd7Btnr3JaKiTBx19Ok89fF73HCKp5krtQkHJhz4fPDUx0aOPmYSUVGxgDx/u3a1nrP2X66s7Phx9Xoa2sFbO4NnZkJysq7h+e6jT7rHAc5yfLWl1DvrqSeeel8U9dV6PB7/WIEYmpnNGrGJPuLjPNisGlaLj6j674ne+Xf0Vd/J9zPFQcGVGHL/jxhD69eBBc+9wczfP8iILAN3ni0mO3eeXcvCjz/mhLc/ZP4jtzP90tPFHdcUDwmHSR63IYJNhQJYsWIFH320BJntbsuE8nY+/HAqX3/9dZ+d9b7nnj9TXz8Ur3cyfqcFh8OEwzEFg6GQe++9r8+byA1U+sr7dF/FZDIRFRWF1Wrt1PNcW1tLWloaAOXl5UR3Yie3z/0OTSawxUHcYNls9UeT1ZfL581xIsIj8cQm7RhIPRoqvoRNT6KrXo9h24sYdr4BeRdD3iUyyx4EJqM+OOFtjAJLVMN7+Q5wl4EtB6JzlADvIfrc/1w/JJjnP2jhvXXrVs4999xWt5933nnccccdQX2vuro69C1ydQwGQ4cGbsXFxezdu5dBg8Ls6NgHaJk33fKyy9U0Nx1oQuYX1Zom7yWa1lpMt+XqPdD59a9vZto0cVSeeymgl+duV2U6O3Zn8OfF+WwoHkJy3vVcd50I6927DzwLHR/ftoFZVpZEcvWlzoCO0DTpkHC7wVVXj9u+F3dNOXjr0JmjMVtTMFt8xNp8xA2qJyZaw2L2YbU2fWx8ubBvg03zJW4FxABm8EVQcEW7Zmcrv1rHzN8/yA2nw9xLvazaCnuBIwrghr96ueklmHHbg4wuTGXcSWdDVK7kxfYh7r57NjpdMppmAT5o4x5WdLrkPutw3tw0Tk8Li8N+YyKnUISLyy+/nGeeeYYzzzyzU/evq6sL84oiBJ1OhKI5QUwz6/dLB5ZjF9TulM1XcwIYetDdvDPodJB6HKQcC3tWiAlbzUbY8gxsfw3yLoW8i8AYE951+LPVPXVg3wKOYrBlQ3SudLApFAqgC8I7JyeHTz75hMLCwma3f/zxx+Tk5AT1vc4991weeOABcnNzGTVqFGvXrmXOnDlcddVVANjtdmbPns0FF1xARkYGW7Zs4fe//z2FhYVMnDgx2KX3CQLjsVo6egeKaX+FOlBI+x29/dVpvb55W7cS013D3w5eWTmek09ewWMffsdzn+cTYy1gv2MYLtekZvdfubL511sszSvWLUV2n2kH7yT+XPT6+qYNH59P/h5NRjdm316itFJiY/YTm2vFEh2D1erDarFjsfg63mhwVsCWp6H47QaTNb3EqxReC7aOkw/mLXiFEVkG5l7qbTMDet5l8Ml6A/P++TnjJt0cyqekR/B6vXz99ZdoWh3QfhuppsFXX63C6/W26ZMRybTeWPC34ixFuj769saCQhFuEhMT+eqrrxgzZgxnnHEG6enp6AJOBnQ6XWNHo81mo6ioqPHygEFvlMhKa6pEe7n2Siu6s1zitfzZ4bogKsPhRqeDtAmQOh52L5MYMvsW2PwkbF8E+ZdB7v9JhTqcGKPk8NQ2CPASiGqogEdgAohC0dMELbxvueUWbrzxRtatW8dxxx0HyIz3Cy+8wN///vegvtc//vEP/vSnPzFjxgzKy8vJzMzkuuuu4+677wak+v3DDz/w4osvUllZSWZmJqeffjr33Xdfv8vy9hviffFFc/dvf2XaT3t5036BrcR08AS2g/ujtvz51iUlLdvBxwHjsDvB7vTf5sNq3Uturpnhw+NbVa6T+2HkpcfTJK79h//v1GSSw2KRnz0mBmwWDxatHKt3GxatHHNUFJgTG05cPB0+ljygHYpehm0vy0wZQOrxMGymnBgdAIfDydsffM6jF/vQ62HFz80zoFf+AuOHw7QTvdy66H0cDkefO9E0GAzs2lXGE088wR133MHQQQZ+fayXvBTYVgGvfmlgU5mXv/71r8yYMaPPie62NxZswCJgKjT4LPTljQWFItz4zWvLysr46aefWn0+UHjr9Xry8vJ6cnmRh8EKUVkycuSukip4bTHUFYsPiTmxS9ngYUOnh4yTIf1E2LUUNi+E2u2w8XHY9grkXw65U8NfuTdGy+GxSwW+rjhAgAfX/q5Q9CeCFt6//e1vycjI4G9/+xuvv/46ACNGjOBf//oXkyZNOsBXNyc2NpZ58+Yxb968Nj9vs9n48MMPg11in8QvvF0uEdJWqxLToULTYN++5vPVgSJ79+7mpnBt4W8HD6xcJyfXERW1iuHDjyY+PrVnfpgexOdrLqxdrqa2eYNBMtHNZkhJgdhYyfW2WORv12qVz+nwyYmKfZt8NFklgqSz+ak+N+x8E7Y8K61/APGjYfgNkHRYp3+W6ppavF4fQxoiT+9+Q49BLxnQBv1w7n7jBz6900dBGni9Pqqrq/uc8Ab44YcfuPPOO7lxIo2VfT93T5F2+jvuuIPjjz++z2Vd+zcWampqGm/zer2sXbuWn3/+uZnIjo2NVaJboWiDjkb5FB0Q2IoenQeuPdKC7qwAzSft1MaYyDlh0+lh0ERIPwXKPpROsbpi+GUebHsJCq6E7CmNJqZhwxgjh9sONb9A3U6IHiwmbKYwt78rFBFIl6ZHp0yZwpQpU0K9FgXSdqxSz4Knrq61cVngZaez46+3WGDQoPbbwWPaeH/w+UyUltYSGxthM19B4vU2CWuXSzaB/PP/fnEdHw9xcfK3abU2CWyLBfRtddtpmpyY2ItkRk5vBNugzrvEaj7Zrd84X1rVQGauh10P6ScFfXITFxuNwaBny24fK36GZRt82GySAe313cVn66ey8hfYWg4Ggz6iExA6Yt7cOYzINjD3Uk+r34te39BOv8HAvLlz+5zwBoiLi2v2u3G73axdu5ZBgwYpcxmFIsS43W6eeOIJAGbOnKn+x/wYLCIcbZmyIezYBXUl4NopbdbmhMhxRNcbIetsEeGl/4HNz0iG+YZHocgvwCcBYd6oNMXI4a6BqvVQuwNiGgS4sZ/N2ykUHRAhrwwKRcf428H9grqlsN6/v+Ov1+kgLa21gVlgO3ibArIf4fcIaDl7bTCIgDabITUVEhKaui78R6cN3jRNIlns2xoEsw5s6aAP4oRt72r45R9QvUGuW5JhyLVyctDFkxmbycvk04/k6WXf8s4araHafTawBDgHg34Ed//7F3bb9UyZPKlPVrsdDgdvv/NOYzt9W+j1MO0ED7cuWtwn2+kVCkX3cbvdPPvss3zzzTfs3LmTJ554gqFDh/Kvf/2LMWPGMGLECADq6+sb286nTZumhHdLdHp5f7IkQ0x+QBV8t3zenBA5olJvlPfQzLOg+F3Y+pysc/2DsPVFdPlXodMODf86TLFyuKuh8n8iwP0V8HDPnysUEUCnzmKTkpLYuHEjKSkpJCYmNjPiaMm+fftCtjjFwEHTRDy31QpeUtK5dvC4uNai2h+9lZEhwnIg4I+H84tsv+meX2D7Z6/j4kRUB4rsbm0+1FdC7TbZ+de8YEkJro2t+heZQ6v4smHB0VBwGQy+pOvu4l6XnAzpTdx0w0yOP+s3rAfgPpoyrvV4fffx2YapgI+Fi2a1990imurq6mbt9O3R19vpFQpF19m6dSunnnoqFRUVHHrooaxcubJxfGP58uUsWbKE559/HpDxDn9E7IFGN77++msAVq9e3Se7abqNMQqMg8XJu77BjM2xW4zZjNESTxkJVXC9CXIvEFPS4rdh6/PgLMO44QFO1mWgK70Ocs7q/DhYVzE1xLS5q6HypwYBnifz9H0sTUShCIZOvQrMnTuX2NjYxssdCW+Foj0cjrZbwTvbDm42N7WDB1au/UI7dgD5dfijufzVa7/A1unE2MxslrbwjAx5XvzC2mYT4R3Sf2F3jbxp1u0Abz1YU4Izbqkrhc0LoHQJoIHOKOYvQ64W45qu4POAq0I2AGzZEJPP+DOTGDbsr2zcqAMm0zyKagowgmHD6LMnjXFxcY3t9B3R19vpFQpF17nxxhtJTU1l9erVJCQkYA7YkT7hhBMazdcArFYrr7zySqe+7333PcCMGdO5774HWLLkvyFfd59BbwBrmhwxdnFCr9sp7eg6vbynRYKwNFhg8IVSBd/5JtrWF4mp3wXrZ8P2FyQpJOO08Dq363QyG2+KE+O6qh/ECC4mT9r4I+F5UihCTKeE9+WXX954+YorrgjXWhR9HI9HKtNttYKXlHS+Hbyt6K3MTDHx6u/t4C3xG5wFtoj73cPNZhHRsbFSvQ4U2I3mZuHcI/PUSltd7Xbw1km7nTWt819fXwlbnoMd/watwV1w0EQY+ltpO+sK/lZ3d620uMcUyJp0elasWMHGjRtoLwMa7mPjxr6bAW2z2Zg8aRJPf/4eN05sPeMN8vf09OfGPttOr1AouseyZctYtGgRKSkpeFu0kWVkZFBWVhb091yxYgUrVnzOjBnTWb58WZ99DQ05/rnm6BypfNeVgGu3dGFFSiSZwQp5l+AZNJmNK59lJG+jq90O398ppqaF1zX4qoRbgCdIV4C7CvZ/L+NqMfkQlRl52ekKRTcIuu/FYDBQVlZGWlrzE+y9e/eSlpbW6oVc0X/wt4MHxm0Fzlzv2nXgdvDY2PYNzAYNGjjt4C0JNDgLjOfyG5xZLJCYKCZnfoMzf4t4j4/deZ0Sp1K7TdrELElS5Q7m67ctgqIXRLwDJB8Fw26A+BFdX5e7WoxuTImQfLjsmAe09g2EDOibZt3MhAlvM+tlmHtp840qnw9uegk2FHv7bDu9QqHoHkajES0wozSA3bt3E9OWk+gBuPvu2RgMBwNgMIzq06+hYUFvAlsGWNPlfcpfBa8rkc+ZE8PvLn4gDDY2m89n2JFXYCp5HYpeAftWWPcHiB0GQ6+D1Anh3c1vJcDXQW0RxAwRc9befo4UihAQtPBu7wXb5XI1a1lS9E387eDtmZg5HB1/vckkAto/W91y5nqgd7d2xuAsJaW1wZk/q71X8dbL3Jp9q1SrzfEQndv5N2KfB0reh81PyY4/yBv68Bsh+eiuv6F7HNJWbrBJ1Fh0Tqsd8oGSAT1+/Hjmz5/PjBkz+Hi9gWkneChIk/bypz83sqHYy/z58/tsO71CoegeJ5xwAn/7298488wz0TfszOl0OjRNY+HChZxyyimN962trW3M8d62bRvR0a2NwlasWMGyZZ9gs70JgNd7O5991nc7h8KKv7XaHC+GYq49EvHlqpDoTHO8zD335jinMQaGXAO5F8K2V+Wo2Qjf3QJxI0WApxzXgwK8EvZ9J5sTsQVgHQQGpTUUfZdOC+/HHnsMkBfoZ555ptmuqNfrZfny5Rx00EGhX6EipHg8UF7evonZgbzxdDpxvm45X+0/BmI7eFv4Dc4CBTb0gMFZOPB5wFHWILj3yolBMIJb06D8c9j4hOxeg1Sjh/5WWsu72sLmc4Nzj3x9TIG0pZnaHvQfSBnQ06dPZ/To0cybO5dbFy3G6/VhMIhb+8JFs5ToVigGMA899BDHHXccI0eO5LzzzkOn0/HEE0/w008/sWnTJlavXt3s/hUVFR1+P6l2j6FZSoRhtKp6HwiDWYzEAiPJHKXilWKwidAMJg0k1JhiRWQPvhCKXoYdr0H1eljzO0gYIy3oyUf1gABPFAFeXwn71oA5qWGELEMJcEWfpNPCe+7cuYBUvJ988slmJ6Zms5m8vDyefPLJ0K9QERSaBpWVreer/R870w4eE9O6DTywHdyiun2Apllru72pPbylwZnVCunpPWBwFg58XnDukixu5x5xbY3KCU4o718n0WCV38t1U7yYpuVOBX0X3zQ1r8zLeetl/is6X+bLD/CEDqQM6HHjxjFu3DgcDgfV1dXExcWpmW6FQsFBBx3EmjVruPfee1m0aBEGg4H333+fU089lVdeeYUhQ4Y03tdms/HTTz81Xm6Jv9rd5JsBoMfrvUdVvTuLTifjWpakhkiyCmlDd5bLSYY/kqy3ThjMCTD8esj7NRT9UzxZKn+Ab2dC4mEwdDokHRbeNej08vyYE2STIlCA2zJ6d4OiF3E2OBI7nc5+dw7Tn+m08C4qkkrVSSedxFtvvUViYhfdhhXdxuls3xm8tBTq6jr+en87eEthrdrB28fjkefdH9Pl9Ta9D3q9vWhwFg58XnCVi7mJc7fMVUVlBheFYi+SaLDyz+W63iJv3PmXi9lMV9A0aTtz14AlFRIa3nR725wmgrHZbEpwKxSKZuTn5/Piiy8e8H56vZ5Ro0a1+3l/tdvrnUzLlAhV9e4CRhsYc6QS7tonnWaOUtloNkWDKaH3IsksSXDQTZB3qfiz7HgT9n8Hq6+VynfhdEgcE941+HPTzYliorr3G4ktjckfUAJ85cqVzJs7hw8/+oiXX36FzMxBTDz9dGbdfIvqaOsDBP0f/Nlnn4VjHYoAvN6228H9H/fuPfD38LuDt2Vilpoage3MEYLX2ySuXS5pGdc02aywWMTYLDNTBLbJBN98A8cdJ7f3eTSf7LLXbpP8UYNJDE2CeaN37oHNC6H4HcAH6CH7PIkmCcbxvCVuu5x8mOMh8VA5MRkgb7IKhUIRKk4++WTmz5/f5mjgxo0bmT59Op9++ukBv0/ranfzlAhV9e4GOr0YllpTZK7ZuadFJFmCdKD1BtYUGHEr5F8GW56XLPC9q+VIOU7a0+Pb36wJCTq9CG5zIrj2w95vZV0x+dKCHgl56WFiwYIFzJw5kxHZBu6fKudA90/1sfCT9zj++LeZP38+06dP7+VVKjqiS3+dxcXFvPvuu+zYsYP6+vpmn5szZ05IFjaQ2LMHbrvNwLp1x7Jnj5HduzvfDp6Z2WRk5hfZqh38wGiaCGuns7mLuF4vz53VKhsUgTPY/hZxP+6GBKw+3+Gj+eSNvXabvLHrjQ27x0G8PLjtUPSiGLH4XHJb2gkw7Hp5M+wqXqeszWCD+JEyW95bJxwKhULRx1m2bBnV1dVtfq66uprly5c3Xne73bzwwguARMkGtrMOhJSIiMAYDTHRErHp2gt1pRJJ5qyQ7jFzPOh6wZPEmg6jbof838DWZ8U4tWKVHGkTZAY8bnh416AziODWvNIhsPfbpgq4Nb3fCfCVK1cyc+ZMbjhdY+6lHrx6E/8FZpwGN5zi4aaXYMaMGYwePVpVviOYoP8qP/nkE8477zwKCgr4+eefOfjgg9m2bRuapnHYYWGe8+inmM3w4ot6oKkiGNgO3lautWoH7zx+gzO/0PbHdLV0EY+KahLYVmsfbBEPFk0TV9Xa7dLSptNL9nUwlWRfPex4Q/I+3VVyW8IYcSpPHNv1tfk8Un0HiMmTOW5zfNe/n0KhUCgAMclti1WrVjWLiq2vr+faa68F4Ne//nWj8B4oKRERhd4o78+2hkgyRzk4ikWI640NkWS9kHcdlQkH/wkKroTNT0PpB1C+XI70k0WAxw458PfpDjoDWFPlvMHfgm5Ng+i8BgHeP/725s2dw4hsA3Mv9aDXt+gx0cO8y+CTDQbmzZ2rhHcEE7Tw/uMf/8itt97K7NmziY2N5c033yQtLY1LLrmEM844Ixxr7PfEx8Ndd3mprv6ewsIxFBQYSU2NgPioPkbLOexAozOrVZ7nwYMhOrq5wB5wz7Omyc557XZwlAA6edMKxuxM80HZh7BpgcyggbzJDbteKt1d3bXQfLJz7XVIm3tMgexg9/tdEIVCoQgPf/3rX/nrX/8KiOg+6aSTGqPE/LhcLjweDzNmzGi8zWAwMGnSpMbLgbcPlJSIiMQUJ0fM4AYztmLZqPbVN32up71PorJhzGwR4FuehrKPYPensPszyDhNxs1i8sK7Br1RBLfPIwksfgEekweWtD4twB0OB2+/8w6PXuxrd1RUr4dpJ3i4ddFiHA6H8neJUIIW3hs2bGDRokXyxUYjDoeDmJgY/vznPzNp0iR++9vfhnyRA4Fbb/WxbNlOkpJG94954TDi9TZVsZ3OppZvo7FpDnvQIJnD9gtsm60ftIR3F02T3WD7DnCWyHVLipinBUPFV/DLY5LtCWJ0VngdZJ3T9dYuTZOKeX2VmKckHNwwq9V33ygVCoUiEjjuuOO45ZZb0DSNP//5z1x88cVkZ2c3u4/ZbGbEiBGce+65jbdZrVbefvvtNr/nQEqJiFj0DT4s1gx5/3TuFhFeVyzv6+bErqeHdJWYPDjkgYYK+EIR37s+gl0fQ+aZkhEenRPeNeiNUun2eWRjoqJcOgWi80SI90FD1urqarxeH0PSO75fQRp4vT6qq6uV8I5Qgj5Ljo6ObpzrHjRoEFu2bGl0vTxQ3qNCEQz+OWz/4Z/D1umkUm2xSPt9fHxzgd0nncTDiaZJBEftDqlwa54GwR1kW1rVBtj4DzFRAZk9y78C8i7uXoubp7ZhXi0OEg+RnfNgNwMUCoVC0SYnnHACJ5xwAiAV72nTppGZmdnLq1KEDJ1ODNfMCSIuXXtEfLsqJKXEHA/GmJ49MYothEMfhupfYPNT0npe+h8oWyKb9AVXS5t6OPH71fgFuGO3XI/OBXNyn8oBj4uLw2DQs2W3r8P7bS0Hg0HfbFNMEVkELbyPOeYYVq5cyYgRIzjrrLO45ZZb+PHHH3nrrbc45phjwrFGxQAgcA7b5QKfr+G9xCwCO3AO2292ZrUqd/YD4hfcdcXy5mPtguCuK5aW8rIP5brOBLm/giFXyRt9V/G6GozTzGLCEpMnYl6hUCgUYeHzzz/nwgsvbFN4B+NqrohQDBbZvLZlyvu/Y5eMg9XuEGNSc2LPmo7FDYfD5kDVetj0pJivFb8DJf+B7ElyHmE9QBm3uzQKcHeDAC+Tjf6oXBmzM8VFfLXGZrMxedIknv78PW6c6Gnz3Nfng6c/NzJl8iRV7Y5ggv7vmzNnDna7HYDZs2djt9v517/+xdChQ5WjueKAeDzNBbbHI7f757BjYyEnR1zbA6vYakQsSOqrGircO8HrlvZtY5AvxPX7xTRtxxtSJUcHmWdA4W+7t1Pt333WfPLGF5snJwMKhUKhCCvBuJrX1dUxcuRIANavX0+UmoPrO/gzry3J4vLtqpBzAuduQGuIJIvpufXEj4QjHoP9P8DmJ6VzbuebUPwu5JwvrenWlPCuQW8SAa55xaCu6kewW8CSLhGlluSIjim9adbNTJjwNrNehrmXIil+Dfh8cNNLsKHYy8JFs3ptjYoDE7TwLigoaLwcHR3Nk08+GdIFKfoHPl9zJ3F/HrZ/DttqhfR0cWdXc9ghxF0NtTuhbodUlC3JYA3yZMnjgG2vQNFL4K2V21KOFeO07sSDaD6ZMfc4ZIc7pqBh3iqyd5oVCoWiP9FZV3NN09i+fXvjZUUfxRgFxlywZcl7sKNUKuGuvSK+TfE0U3HhJHEMHDkf9n0nFfD938GOf0keeO5UyL8cLEnhXYPOIJv95kQ5H3GUSmefOR6icpqq4BHG+PHjmT9/PjNmzODj9QauPQXyJsP8pbDwEyMbir3Mnz9fOZpHON3qN7Hb7fh8zecN1FzBwELTWreJt5zDHjSoaQ7baHQTF2fCYlF6K6S4axoE907w1jUI7rQDf10gPo+8+W15Wt6QAeIOgmE3QMrR3VtffRXUV8obatJIMYTpZxmbCoVCEYl01dXcarWyevXqxsuKPo6+IXbLmgoxQ8QJvW6niHBfD5+QJR0GRz0F+74RAV75g2z473wLci+E/Eu7N8rWWYw2OTSvnKfs/wGMVrBkSGefJTmizlWmT5/O6NGjmTd3Lne9sYSXJ8Ndb+g5Y+IkFi6apUR3HyDov6aioiKuv/56li1bhtPpbLxd0zR0Oh1er7eDr1b0ZVrGdfl/1f457MREmcOOjm6aw7bZmuawV61axVlnnc0HH/yXY489ttd+jn6F2y47tbXbRXCbk4Jv19I0cR7d+IRUykF2xofNkBiQ7jiAeuqkxc0QLfne0dm9kzWqUCgUA5SuupobDAaOPPLInl6uoicwxcgRnSvv0dXFQAnUlUBUUs/4reh0kHwUJB0JFV+KAK9eD0UvwI5/i3Fr3iVgiu2BtRikMGBJkvMWR0PnoDkhoAreA+voBOPGjWPcuHHU1NTw6aefUlpaRmxsZKxNcWCCFt6XXnopmqbx3HPPkZ6e3m7LkiI4vvnmawA2bFjN4Yf37o5VZ+K6MjNbx3UZD/DXdOedd1NVVcmdd97Np58uDf8P0p/x1Irgtm8Hj13eLLoyH7VvrUSDVf0o100JUHgN5FzQvVknX70Yp+kMEFMoxmkR8qalUCgUA4mWrubXXHMNWVlZvbwqRUTgNx4zJgMlEJ0P7lLxeDEn9pwATz1ORtr2LIdNT0lc6ZZnYPtrkHcp5F3UczPpxig5fB6Jaav8HgxREklmy5QCRwRUwf1dKKobpW8R9F/O999/z5o1axg+vBuznopWPPjgA9xww3Sef/4BDj/8vz3ymG3Fdfl8UqG2WuVoK67L0oWkpxUrVrBs2SfAZXz22UusXLmS8ePHh/xn6vd46mRHunabtJdbEsE6OPjvU7MFNj4Oe1bIdYNV3tzyL+3em5vmld1zr1vatGIKpFVLoVAoFL3OPffc0+n7ejwe/vWvfwFw4YUXYjzQ7rqi75MwErS8BnPWYnDtk439nhLgaSdA6vGw+zOJIbNvFTO27Ysg/zLI/T8RxT2B3thkUOeplefEvl02JKJzJZbV1IMGdYp+QdCvokceeSQ7d+5UwjuErFixglWrPueGG6bz/ffLWLduJWPHhlaUut1NFey24rqSk5viuvwCO5RxXXffPRuDYQxe7/MYDOu4++7ZquodDH4DEPs28FRJZTo6N/hBeeduaecq+Q/gk4p09mQYMq17jqL+rHCPHSypkDhEDNS606auUCgUim5z3nnn8be//Y2hQ4dy3nnndXhfnU7HO++8A8jc96WXXgrA5MmTlfAeKJjjwTxazjF6RYDrIeMUSD8Jdi2FzQtlnG7j4zIHnn+5GLH15NiaMVoOnwfclWIKZ4iWboHGKriK31EcmKBfRZ955hmmT59OSUkJBx98MKYWNtRjxowJ2eIGCiJKDwbAYBjFk0/O5sknuyZKvd7mVWx/m7jJJAK7rbguq/XAbeLdoana/SZgwOu9h88+m6qq3p3B64S6UqgtEuMPc7xEcAUruN3VsPUF2P4v8LnktvSTYegMaQPvDu4aEd2mODFMsWVGdCSHQqFQDCRqamoa/Xeqq6s7PSKo1+s59dRTGy8rBhiRIMAHTYT0U6DsQzF+rSuGX+bBtpckgix7imSXdwKHw0l1TS1xsdHYbF0U7XqjVLotKVJoqN0mmwKNVfDUnqvIK/okQcutPXv2sGXLFq688srG23Q6nTJX6yJ+UWqzvQmA13s733479YBVb3+buL+CXV8vtxkMTXFdqamt47rM5p76yZpoqnZPbrhlCgbDaFX17givCxxl0mZVXwnmuK5VuL0u2PE6bH1exDdA4qEw/EZIGN3NNTpljttgk4zOqNzgs8IVCoVCEVY+++yzxsvLli3r9NfZbDaWLlXv0QOe3hbgeiNknS0ivPR92PwsOMtgw6MSe1pwJWRPanfDf+VX65i34BXe/uBzvF4fBoOeyWeewKwZlzDu6LFdX5cxRg6fR87T9q6R67ZBcliSVNefohVBC++rrrqKQw89lEWLFilztRDgF6VwNrAEOAeDYXSzqndgXJfT2RTXZbHIkZYmc9gt28Qj4VfTvNrtfwHSq6p3e3jr5Q3FXiRVZGMMROcE/+KteaH0A2krd+6S22IKJBosdXz3/jh87gbjNJ1Uy6Pz5Y1ZoVAoFBHN3r17SU5WvhuKLtBKgJf0vADPngyZZ0PxO7DlORmfW/8gbH0RCq+GzHOaGZ8teO4NZv7+QUZkGXj0Yh9D0mHLbh9PL1vO8Wd/xvxHbmf6lVO7vy5rCmgNs+D2rdKlaEkWR3RLiqqCKxoJWnhv376dd999l8LCwnCsZ0DRkSj99tupfPjhSkaOHI/JJEI6Ph4GD5a4rkCBbYjgsZLW1W4/qurdDJ9bsjTtW6F+n7yJRWV3QXBrULEKfvkH2DfLbdZ0KLxOdox13fhj0XyS7+11yVxTTIG8oUTCDo9CoVAoDkhqaiojRoxgwoQJjYdyOFcERa8LcJPMeGedC8WLpaPPWQY/3S8jdUOugcwzWfn1j8z8/YPccDrMvdTbzLPoxolebnoJZtz2IKNHFnav8u1Hp2uKafO5G6rg30qiiy1TzpvMiaoKPsAJWniffPLJfP/990p4h4DmojSwRV9E6fvvz+bqq5c2imxTHxubbXtjwY+qegPSouTcJRVuZwWYoiAqq2sCuep/Eg22b41cN8ZCwRUw+MLumZBomkRq1FfJDm7CaLBmKCMRhUKh6GN88MEHLF++nOXLl/P888/jdrsZPHhwMyHuP7+rq6trzPH+5ptviIpSVTtFAM0E+M6eb0E3WGDwRVIF3/EGFL0oM+A/3gtbn+ebj6IZma1n7qW+VkbBej3Muww+WW9g3oJXQyO8mz2ASbK/NU1mwWs2S2HFkiJFFUuKGs0boAQtvM8991xmzZrFjz/+yOjRo1uZqx3IMVMhtBalgcJbROmXX05l06a+K0rvvns2Ol0ymmYBPmjjHlZ0uuSBWfX2eaRFyl4k8VsGK0R3UXDX7oRNT8Cuj+W63gy5F4ro7m4LuKe2YUMgDhLHyhuGoReMAhQKhULRbSZOnMjEiRMBcS3/6quvWL58OUuWLOGll15Cp9Ph8XgA0DSN9evXN15WKNrEHC9HdI4I37qdDQI8sWeytw1WiULNOV88bYpegtrtzBoHl41pP51Hr4dpJ3q5ddEyHA5n1w3XOkKnk4q3KRZ89VIF31cGxriAKniCqoIPIIIW3tOnTwfgz3/+c6vPKXO1ztNalPrf1JYCOvq6KPV6vXz99ZdoWh1wTrv30zT46qtVeL1eDJHcMx8qfF4R3LXbwFkuO7a2Qc1mkjqNay9seQZ2viUz3ehk9mnodHkx79Y662V9ehPEHQQxg3tmB1uhUCgUYaeuro4vvviC5cuXs2zZMtasWUNMTAzjxo1rvI/Vam00ZrNaezC6SdE38QvwqOwAAb6/5wS4MUoKDrlTsf/vOTyb/0lKbMdfUpAGXq+P6pra8AjvQPRmsKY1VMFroGYj1LaogvdkRJqiVwj6bN/n84VjHQOKtkWpDVgETAUcQN8WpQaDgV27yqipqTngfWNjY/vczxc0mk+ErL2oQXCbui64PbVQ9DJsexm88rdC6jgYdj3EDu3+Ov1z3FGZEDNE2sYUCoVC0ef5wx/+wPLly/nuu++IjY1l/PjxTJkyhXnz5nHooYc2iw0zGAyceOKJvbdYRd+k1wV4DIZh1zJ40kv851aNYzqYjN1aDgaDnrjYHiws6HTSRWiKk3Ot+n2SYmOMk1FDWzqYEpR/Tj8lqLN+t9uNzWZj3bp1HHzwweFaU7+nLVHq9XpZu3YtP//8czMR2pdFaVxcHHFxcb29jN5F84kDeG0ROHaL0LZldE1w+zxS3d7yjLxQg8R4DbsRko/o/lrrq6QNypIMCWNknar9SaFQKPoNjzzyCDabjenTpzNz5kyGDRvW20tS9Fd6UYDbbFZOOuFErn56OT/+1dtmu7nPB08v0zPlrBPDX+1uD4MFDOlyruiugeqfwb6lRRW8cznlir5BUGf/JpOJ3Nxc1U4eAlqKUrfbzdq1axk0aFCruXlFH0Tzyex27XbZydTpZReznZzJjr+XJvPbm+bLGxdIRMWwmZB+Svd3RRvzuKNEcEfnqBd6hUKh6If8+9//bjRXmz9/PmlpaRx//PGccMIJTJgwgVGjRjXe1+Px8P777wNwzjnnYDR2YcNYoQicAa/dGTADnhRWAX7Tby9hwjmfMetlmHtp61lvvR7mX+Ej6cgQFC66i07f9Dx5XXL+WFcK5jgR4NZ0MMWrKng/IOhX0TvvvJM77riDl156iaQk1YKqUDRD0wIEdymgE2dLfRcNyfZ+CxsfgyoxuMGcBIXTIHtK16rmgfg84Nojl2MKICZfDEAUCoVC0S+54IILuOCCCwCoqqpi5cqVjQ7n119/PcnJyZSXlwNivjZlyhQA7Ha7Et6K7mGKg4RRPSbAxx8zlvmP3M6M2x7k4/8ZmHail4I02FUFURYdvzpK44QRgP1h+GYZFE6HxDEhX0fQGCzScaj5wF0t5381m2U+3JbVUAVXJrd9laBfRR9//HE2b95MZmYmgwcPJjq6+VzEd999F7LFKRR9Bk2T2ehGwU33WoRqNkkWd8UquW6wQf5lkHepGIh0d631+8BTJ7uosYUqj1uhUCgGEG63m59++okffviB77//np9//hlN09AFvA/o9XqOO+64xssKRUjoQQE+/cqpjB5ZyLwFr3LromV4vT4MBmkvH37WGRwZ9zUUvwN7V8uRchwMvQ7iRx34m4cbnV4cz80JDZ2J5VBXIs9fVA4YVPGzLxK08J48eXIYlqFQ9GHq90N1CThLZIfSktx1Z0rHLti0AEr/C2gSL5ZzPgy5Rr5vd3HbZYPAnABJh0mcRXcr5wqFQqGIWAoKCli8eDGHHHII99xzD8uXL2f16tU4HA6ysrKYMGECjzzyCBMmTGDEiBGNX2ez2fjiiy96ceWKfk0PCfBxR49l3NFjcTicVNfUEhcbHTDTfTLkXw5bn4WS96XYUbEK0iZA4XUQNzxk6+gWBmuLKvhPQEPV21EG+jTliN5HCPqM+5577gnHOhSKvoWmiREZyC6pzgvWbkRB1FfB1uclg9JXL7dlnAZDfwvRud1fr9fVMMdtEUO26MFgtHX/+yoUCoUiotm2bRsulwuAV155hQkTJnD55ZczYcIECgoKenl1igFPKwFeHBYBbrNZ2zZRi8qEg/8E+VeIeW3pB1C+XI70k0WAxw4J2Tq6RWAV3FUH7IO9a6A2VpJyrGlgTlQFlQimy7+ZNWvWsGHDBgBGjRrFoYceGrJFKRQRi6ZJhbtuB9QUy23GOLB2MYrC64Ttr8HWF8Bjl9uSDofhN4am1Unzysy51y0GHbFD5AVboVAoFAOOzZs39/YSFIq26SEB3i7ROTBmNhRcCZsXwq6lsPtT2P2ZFEIKr4WYvPCvo7P4Cz1RmUCdzIHXbJZzPFuWFIOUIVvEEbTwLi8v56KLLmLZsmUkJCQAUFlZyUknncRrr71GampqqNeoUPQ+/rno2p3gKBFjMmMisL9rlWPNK21Nm54ClxjZEFMIw2+QGaNQvFDWV4K7CixpkDhE5rlVPJhCoVAMOHRdeE9xOBxMmDABgOXLl2OzqS4pRQ/Q2wI8Jg/G/gVqrhIBvvtT2PWRpMtknimjf9E54V9HZ9HppQBkipNzU3c1VP0INWYZUbRlNTx3PZhVrmiXoIX3DTfcQE1NDf/73/8aZ4HWr1/P5Zdfzo033siiRYtCvkiFotfwC277DnCWguZpME2zgscH7A/+++1ZARsfB/tWuc2aAUOnywu6LgSZ7Z46qXIbYyFhrFS6lQOmQqFQDFhOOumkThmk6XQ6qqqqAPD5fHz77beNlxWKHqU9AW5OAlMPCPDYQjj0Yaj+BTY/Ja3npf+BsiWQdY4IcNug8K8jGPRGEdmWJOmorN8nM+CGKIm0tWbI86fOCXuNoIX3kiVL+Pjjj5sZcIwcOZInnniC008/PaSLUyh6jUaX8p0NpmneJsHdVSp/hF8eg/1r5bopDgqugtxfhSY32+cR10udXqrnMfk98+akUCgUiojm4osvJjs7O6ivsVgsjTneFksI3qMUiq7QTIAXiwlbfQ8K8LjhcNgcqPqfdClWrBIn9JL/QPYkGHKVdBRGGgarHJoG3lqo3QH27RIba8uUqFtzouqE7GGCFt4+nw+TydTqdpPJpHZEFX2fwFgwZ1n3XcoB7Ntg0xMyJwSgt8Dgi6DgcnlD6faafbIL7HXI7mvMEFmzmutRKBQKBTBt2jSOOuqooL7GaDRy9tlnh2lFCkWQmOIgYSREZ/eOAI8fBUc8Bvu/lwr43tWw800oflfSZwqulLnqSEOnkxZ9Y4wUkdw1UP2zxNaaE6Ur0pIsglwRdoIW3ieffDK/+93vWLRoEZmZmQCUlJQwa9YsTjnllJAvUNF/cDgcVFdXExcXF3mzYpom7dm1OxpyuLXuC25nBWxZKDujmhfQS3tS4bUSCxEK3DUNbzzJsiNsHQT6ELSrKxQKhUKhUEQavS3AEw+BI+fDvjVSAd//Hez4FxS/DblTJZ7MEqEZ2zpDkyu6zy2JOvu/A4MNLKlSvOnuua+iQ4LuL3j88ceprq4mLy+PIUOGMGTIEPLz86muruYf//hHONao6OOsXLmSqRecT2xsDBkZGcTGxjD1gvMjIx9U80l79r5voeJLEd2WZIjK6voLj8cuWdwrJsPOt0R0px4P416F0XeHRnR7ndIG73VB/MGQcrTsWirRrVAoFIoQ4PV6Wbp0KUuXLsXr9fb2chSK5vgFeOqxEDu84bxoB7jtPfP4SYfDUU+JCE8YAz4XbHsFlk+CXx5vipyNVPQmqdBHDxZPIOduqFgN5Suh8ieJoPV5enuV/Y6gK945OTl89913fPzxx/z8888AjBgxglNPPTXki1P0fRYsWMDMmTMZkW3g0Yt9DEmHLbt9PP35exx//NvMnz+f6dOn9/zCNF9DhXu7GE+ga5jh7sYcm88NO96UHEh3pdwWP1qiwZJCFLfn88i6NS9EDYbYAjDHh+Z7KxQKhaLfcc899wQ93w3gdDobvXvsdjvR0e27ItfWyke3G9qYRlQowkdjBdxvwtaDFXCdDpKPgqQjpXiz6UmoXg9FL8COf0PexZB3SeS3cRttcmg+KR7VbJFDRZOFnE4J76SkJDZu3EhKSgpXXXUVf//73znttNM47bTTwr0+RR9m5cqVzJw5kxtO15h7qYdAQ9UbJ3q46SWYMWMGo0ePZty4cT2zKM0nu3i128G5C9CJwYS+Gw6Pmg9KP5Iqt6NEbovKhWHXQ/pJoXmh0jQR8+4aMfGIGQLWNPUiqFAoFIoOueeee7r0dXq9nkMOOaTxckfs2ycfv/0W8vMhI0MJcEUPY4rtXQGeehykHAt7lksLes1GKcRsfw3yLoW8i3omDq076PSykdFuNFmmfFTRZF2mU8K7vr6e6upqUlJSePHFF3nooYeIjY3w3RtFrzNv7hxGZBtaiW4AvR7mXQafbDAwb+7c8AvvRsG9TdppdPruC24g1fs9xtW3Q410f2BJhiHXitOlPuiGkrbx1Mq8uCkeEg+VNni9OqNRKBQKRfiw2WysW7cuqK+pqxPxnZQkAjw9HZQhuqJH6W0BnnaCjBfu/kxM2OxbYfOTsH0R5F8Guf8HxqjwriMUtIom2w91pSK6VTRZl+mUMjj22GOZPHkyhx9+OJqmceONN7ZrjvXcc8+FdIGKvonD4eDtd97h0Yt9rUS3H70epp3g4dZFi3E4HOExXPN5wdUguB27ZQbamtZ94Vr9C4afH+M459fgBAzRUHAZDL5E2nVCgc8t8+d6o8RZxOSpXUaFQqFQRCzJydKgtX9/kwDPy5MKuFX5NSl6kvYEeE9UbHV6yDhFuh53LYXNC6XTcuPjMgeef7kYsfUVE7N2o8liGlrRVTRZZ+mU8H755ZeZO3cuW7ZsQafTUVVVhdPpDPfaFH2Y6upqvF6Z6e6IgjTwen1UV1eHVnj7vOAqb5jh3i3i1ZbefcFdVyIzPGUfoAd8GNFyLsAw9Bp50QkFmk8izbwuiMpsiAeLUIdMhUKhUCgCMBggJUVEd2UlfPcdxMdLBXzQIIi0UBNFP6eZAN8hhRh3dcO4XpgNaXV6GDQR0k+Bsg9hy9NQVwy/zINtL0kEWfaU7vkL9SSdjSYzxqhRyHbolPBOT0/nwQcfBCA/P5+XXnqJ5OTksC5M0beJi4vDYNCzZXfH2e5by8Fg0BMXF4I8a2gS3PZtTdXiUAju+krY8izseAM0tzxU+ul8Uj2FE4cfjsEYol2++ip5LEsyJIyWaAe1g6hQKBSKHsbhcHDmmWcC8MEHHwS9Oa7Xi/hOSICqKli3DoqKYPBgyMyEqD7QbTtQ8BfTnE4npv46nG+KbYhdTYOazVJIMSfIPHO40Rsh62wR4aXvw+ZnwVkGGx6FIr8An9S3xghVNFmXCPqMvqioSIluxQGx2WxMnjSJpz834mtHe/t88PTnRqZMntL9arfPI7Mne1dLHEL9PontsmV074XM64Qtz0k8xPZFIrqTj4JjX8Y7+n7q9IO6t+7Ax6ndKT9HwhhIOUZmuZXoVigUCkWIWLNmDZ988knj9f379zNt2jTGjx/Pvffeiy/gDdvn8/H555/z+eefN7s9WPR6SEyE3Fy5/sMP8MUXsHEj2Hso+UnRNv6418xMOZfJzBwUOXGv4cKaCslHSOqMt16ywH3unnlsvRGyJ8OEt2Dk7WBJE9+h9Q/C8vMlC7wvRnipaLJO0yX3p08++YRPPvmE8vLyVi/GasZb4eemWTczYcLbzHoZ5l5Ks1lvnw9uegk2FHtZuGhW1x/E55F/8Nrt8o9tMDWI7W4am/k8UPKeGGO4KuS22GESDZZyjFz3dP1EpNnjuPbI3ExMvhw9sfuqUCgUigHHrFmzOOWUUzjllFMAuOmmm3j77bc57bTTePTRRzEYDPzpT38CwGKx8Prrrzde7i46nVS/4+Ohuhr+9z/Ytk0EeVYWKM/eniUw7vX+qVKguH+qj4Wf9HLca0+gN0FcoYjFmk3S/m2MaZhT7oEWab1JZryzzoXixbD1eamA/3Q/bH0BhkyDzDM6bIX/es1PQBKrv/uJcUeNCf+aO0tjNJkGnhoVTdaCoMtps2fP5vTTT+eTTz6hoqKC/fv3NzsUCj/jx49n/vz5/OMjHaPvMDLvA3h3Dcz7AEbfYeTxpTrmz5/fNUdzn0fahCq+gr3fSNSWLUOitrojujUNdi+DLy6C/z0gotuWCWPug+NebhLd3UXTZI67rhTMyZBytFS6lehWKBQKRZhYv349Rx11FCCt5G+88Qbz5s3jjTfe4KGHHuKll15qvK/RaORXv/oVv/rVrzAaQ5TSgZxvx8eL4DabYcMGWLVKhHhVVcgeRtEBgXGvP/7Fw4yGdOAZp8GPf/Fw/WkaM2bM6N+VbxAxmHgYJB0O6MWAzduDHlYGCwy+CCa8A8NvEuFfVww/3gMr/0/mwrW2izz3Pfpcw8fne269waDTyTltdLacn/vqJZpszxew92uZt/fU9vYqe5ygX0mffPJJXnjhBS677LJwrEfRz5g+fTqjR49m3ty53LpoMV6vD4NBz5TJk1i4aFbwotvnlgq3fZtUig1WmSMJRXTX/nXwy2NQ+YNcN8XDkKtlV7KbsWPN8NjBuVde8JMPF2EfqugxhUKhUCjaoa6ujqiG4eovvvgCl8vFpEmTABgzZgzFxcU9up7YWDnsdmk937lTqt85OVIdV4SHlnGv3oDP9Xjca2+jN0B0rkRj2TeLINSbwJLSc+N+BivkXwo558OO12Xuu3Y7fH+n+AsVXicO6Q3rWfHlWlZ8uYYZN8LyVd+y8qt1jD9mbM+stSt0FE1mTRdhPkCiyYI+26+vr+e4444Lx1oU/ZRx48Yxbtw4HA4H1dXVxMXFBT/T3Si4i6RSbLCGTrDaiyTiofxzua63QN6vJe4hlJmPvnpwlMsLS/zIhlkYZe+qUCgUip6hoKCADz74gBNOOIFXXnmFww8/nKQkSc0oLy9vZnTq9Xr56quvADjmmGMwGMLnAB0TI0dtLWzZ0lyAJ/ZQ9+9AIWLiXiMNUwwkHCJCsHqjVL8tKT0b42qMgoIrpOCz7TXY9rLkgK/7g4w7Dr0OUidw94NPYzCMAsBgGMndDz7Np28/0XPr7A4to8nqdsgmwwCJJgtatVxzzTW8+uqrjTNACkVnsdlsXRPcjl0S/+CsEKEaqgq3s1yyFYvfBXyAXlwlC6+Vf/xQoXmlZd3rlqiF2ILQRY8pFAqFQtFJbr75Zq655hqeffZZ9u3b16y1fNmyZYwZ0zQr6nQ6GT9+PAB2u53o6PALkOhoOerqZP67uFgc0HNzxSFdCfDu0+txr5GMTifnmOZEKcrYt4pbtzWtZzsTjTFQeA0MvlByv7ctgpqN8N0t1BjysFRvw+t9AwCv9498tmJq5Fe9W9KpaLIkMWvrR//4Qf8VOZ1OFi5cyMcff8yYMWNaxQ7MmTMnZItTDGC89eDc1VDh3ie7gNFZoclcdNuh6EXY9ir4XHJb2okwbKaYm4WS+krJi7SkQuIQ2Untp7t4CoVCoYhsrrrqKgoLC/nmm2847LDDOOmkkxo/l5yczO9+97vG6zqdjsLCwsbLPUlUlBxOJ+zYASUlkgGemysZ4f3oPLzH6bW4176EwQrxI+TcrWYTOErAlADm+J5dhykWhk6XOfCil2HHa8R6t7HkD/Dl5kfxec8Efo/BcHDfqnq3pMNosjSJ1+0nbehBC+8ffviBsWPHAvDTTz81+1xPvzAr+iGBgrt+HxhCKLh99bDj3xIP5m5wcEk4RJzKEw/p/vcPxOOQGXRjQ+tSVHa/edFQKBQKRd+ksrKSCRMmMGHChFafu/fee5tdj4qKYtOmTT20sraxWiE7WwR4aakcGRmSBZ6SQrut0or2aYp7fY8bJ3rafA6b4l4nDZxqd1tYU0Rs1+6Q7O/aYrCl93zetjkBhl/PVxWjWfnaLcw8zcyxhV+B8ys+vO1j7nz9//hsxd19r+rdFv5oMlKkCu7aDb7h/eYcOmjh/dlnn4VjHYqBjrdeohTs20RwG6MacqxDILg1H5QtgY0L5DEAovNh+PWQOiG0W+c+j7Sw6/QQU9gQDxbCOXGFQqFQKLrIoEGDuOCCC7jqqqs4+eSTe3s5ncZqlZZzlwt27YKyMkhPFwGemgphHD/vl7SMew3MOApZ3Gt/QW+C2CFgSZZYrLqdco5q7vnZhz8+/C9WfDmav/33A/50/l+57pSnOH74Cpb/aQUf/xTNa8/PYfwx/+zRNYUVvRm8db29ipCi9goVvYvXJaYKFatg3xpp/Y7KbnCT7OY7qabBni9h1aXww90iui2pcPBdMG4RpJ0QuhdNzSdz3I4ymQVKPhoSDlaiW6FQKBQRw5w5c9i4cSOnnnoqBQUF3HfffezcubO3l9VpLBYR4KmpUFEBX38Nq1eLEPd6D/z1CqFl3Ov8pXL7/KUhiHvtr5gTIHFsQ/SYocejx1Z8uZZlK1fj9d7Lrsosbl00l49tT/L0smup95g49eBaHp+ynn0fXwFV63tsXYrg6HTF+/zzz+/U/d56660uL0YxgPC6RKTaiySD2xgNUTmhm3+u2gAb/wF7V8t1YzQUXClzMgZraB7Dj9sOrv2y+5k0ssFtXW2/KxQKhSKy+O1vf8tvf/tbfvrpJ5577jkef/xxZs+ezSmnnMI111zD5MmTG717nE4nF1xwAQBvvvkmVmuI3zu7gdksLeduN+zdC+XlIsYHD5ZKeAhjx/stgXGvd72xhJcnw11v6DljYhfjXgcCegNE54jpV80WKRzpjT0SPXb3g0+j0yWjaRbgA0DDqU/hdy9P4oHFx3LX5EVcMeEjkvgJvvwNpE2QGLK44WFdlyI4Ov3SFB/fw4YCiv6J1ynZfbXbxHjMFCsV7lC9YNUVw8b5sOsjua4zQe6vYMhVslsZSrwNxmw+F8SPkniwUIt6hUKhUChCzMEHH8ycOXN4+OGHee+993j00Ue56KKLSExM5NJLL2XmzJlkZmby3//+F5BosUjEZBIB7vHAvn1S/U5Jgfx8EeCmHh7F7Wv4415ramr49NNPKS0tIzY2treXFfkYo8Xwy5oG1b80RI8li69PGPB6vXz97Q9omhM4p+FWG7AImMr2CgfTnoG/vguzp+q5ZBzoypdD+XJIP1kEeOyQsKxNERydFt7PP/98ONeh6O94HFLhri0St0JTrOwahkpwu/bBlmdh55ugeQAdZJ4Bhb+FqMzQPIYfzQvOPfJOD5B0JEQnh/YxFAqFQqEIIz6fjyVLlvDSSy/xzTffkJGRwbnnnsu7777L/PnzeeyxxxrP/czm9o2NHA745hsdFktPrbw1RiOkpcnb8v798M03Ej+Wny/CvIPlK6CxmyGSuhoiHp0ObBlS1LFvA/sWqK+RONoQR48ZDAZ2bVhCjb1p3tnr01hb5Obnr97AoG8am4yNiUKnr4AtT0PZR7D7U9j9GWScJnG5MXkhXZsiOFQzjiK8eOoaWsq3iZO4OQ6ic0M3W+2pk1iwon82GTCkHAvDrg99e42myc/grpZ4g7jBwBr5mRQKhUKh6ANs2rSJ5557jn/+85+Ul5dzxhln8MYbb3D22WdjMBjQNI3bb7+de++9l127dh3w+/3733D55Uays09m6lQ955wDCQnh/znawmiUlnOvVwT4mjWQmAh5eRJH1pubA4p+isEK8QdJu3kYo8fi4mKIi2uqqLs9PtYWlTIoIxWTsWURKwYOeUBGLDcvFPG96yPY9TFknglDrpHil6LHUcJbER48dU0t5Z5qMMWHVnD7PFD8Nmx+Gur3ym1xI2D4DZB8VGgeIxBPnZinGWMh8VBxXI/MzjuFQqFQKNpk/PjxfPnll+Tk5DB9+nSuuuoqsrKymt1Hp9MxdepUHnnkkU59z/JyiIrSKC6OZd48mD8fTjkFpkyBQw/tncxtg0Fazn0+EeDffSebAX4BPpATshRhos3osTRx5u4tYgvh0IelHX7zU9J6XvofSfrJOkcEuG1Q761vAKKEtyK0eGqhrkQMJzx2MMVBVAgFt6bJzt3GJ6Buh9xmy4JhMyHj1NCbW/jc0lau00PMUIjNl9keAK87tI+lUCgUCkUYycjI4L///S+nn346ug7el8eOHcvmzZtZt24dAKNHj8bQTmbXrbfCaad5eOqp//Hpp4fwyy86PvgAPvhAzM6mTKHXquB6PSQnS9W7qgrWrYOiIllXZiZERfX8mhT9mMbosRQR370YPdaMuOFw2BxxO9/0pCQJFb8DJf+B7Enig2RN7731DSCU8FaEBrdd2mvsDYLbnNDgUh7CF5p938Evj0HVT3LdlACF10DOBfJiF0o0n8yNex2yGxgzRHYzFQqFQqHoo7zxxhudup/JZCI9PZ0hQ8SQyW63Ex0d3e79Y2Nh4sTtXHHFKH75xcTixbBkCWzfDvPmwRNPNFXBDzus5zWIXi/iOyFBBPgPP8C2bZCbC1lZ0MGPplAEjzkekg4V87WajSLArWm9b8AbPxKOeAz2/wCbn5Tkn51vQvG7kHO+tKarc92wooS3onu4a8RJvHaHVLstiWAdHNrHqNksFe49K+S6wQZ5l0L+JeFxkHTXQP0+2aFMGAXWQSoeTKFQKBR9nuXLlx/wPhMmTACk5TwzM7PxcmfQ6WDkSDluuknE91tvwS+/yOUlS3q3Cq7TyWPGx0N1Nfz0U3MBrgy9FSFDp28RPbatIXosNezRYwckcQwcOV8KWpuehP3fwY5/yQhn7lTIv1zWrQg5Sngruoa7Gmp3iuj21oE5MfS7ZI5dMpNS8h/ABzoDZE+RKrclDDtyXpe0lRusKh5MoVAoFP2OE088EZ1Oh6Zpjbe1FNX+6LCoqChKSkq6/FjR0XDBBXJs2CAC/MMPm1fBTz5ZRPjhh/dsFVynE/HtF+AbNsi6cnIgOxvilGeqIlQERo/VbJJClTUlbNFjQZF0GBz1FOz7RgR45Q+w7RXY+RbkXgj5l4Y+ineAo4S3IjjqK0VwO0qkDducFHrB7a6GrS/A9n9JRjZA+ikwbIaI4VDjjwfTvDKPHlsQcjdKhUKhUCh6m7Vr17a6bf/+/Xz44Ye8+eabPPXUU2F53BEj4M47pQr+4YeweLGI3Q8/lCM3F84/v3eq4HFxctjtUpnfsUOq3zk5vefOruhnNEaPJYK9CGq3Qn21iPEQR491aW3JR0k0bsWXIsCr10PRC7Dj35B3MeRdIjHAim6jhLeic9TvF4dGR7FUhi2JklUYSrwu2PE6bH1exDdA4mEw/EZIODi0jwUB8WBVEg8WWyjmEr1pgKFQKBQKRZg45JBD2rz9xBNPJCoqiqeeeoqTTjopbI8fHS0C+/zzm1fBd+xoqoKfdJJ8vqer4DExctjtsGUL7NwpAjw3VwS4OjVQdBuDRaLHrKkN0WOlYkIcCVVlnQ5Sj5NI3j3LYdNTMp++5RnY/pqMeOZdFBmV+j6MEt6K9tE0Edx1/gp3vcx8WNNC/DheKP0ANi0A5265LWYIDLsBUseF590uMB4sYazM4YTaoE2hUCgUij7Ccccd1yxCzOl0ctlllwHw0ksvYbWGdvQqsAr+0UdSBV+/Xi5/9JEIXv8seGJiSB+6Q/wCvK5O5r+Li0WAZ2WJQ7q+l8dzFf0AS7LE7DZGj+0EW3rvRo/50ekg7QRIPR52fyYjn/atYsa2fRHkXwa5/ydu7YqgUcJb0RpNE3Oxup0SDebzNAjuEP+TaRpUfAG/PA72zXKbNR0Kp0PWWTLTHWp8HnCWN8SDFUJMPpjU7p1CoVAoBjZvv/02SUlNhkper7fRBf2FF14I2+NGR4vAnjIFfv5ZquBLlkgV/O9/b6qCX3BBz1bBo6LkcDhk/nvHDkhNlQ2B1FQwR4BGUvRh9EYZbbQkN0SPFYPRCubkyGiv0Okh4xRIPwl2LYXNCyUqeOPjMgeef7kYsSkvpKBQwlvRhKaBa6/svDlLGwR3MhhtoX+syp9g4z9g3xq5boyFIVfKLlo4/ok1n2wmeFQ8mEKhUCgGJuedd16r2+rr6/nll1/YsWMHDz/8cOPtZrOZxx9/vPFyT3DQQXDHHU1V8Lfekir40qVy5ObC5MlSBU/qIdNlm00M19xu2LcPdu2SCnxODmRkqCgyRTfxR4/Z0qF6o1TBbemRI2h1ehg0UbyWyj6ELU/LJsEv82DbSxJBlj1F2ugVB0QJb0WD4K6Qf3ZnmbR+W1LC809fuwM2zYddH8t1vRkGXwj5V4TP0CwwHixZxYMpFAqFYmBSXV3dysXcarVy6qmnMnXqVCZOnNh4u8lkYubMmT29REAqzZMny/HzzzTmgu/YAY89BvPnN58F74n2b5MJ0tPB65Us8O+/h82bRZQPGiRiPBIKlYo+iE4PUdlyntoYPWaIjOgxP3ojZJ0tIrz0fdj8rGiGDY9CkV+AT1JjmwegV4W31+vl3nvv5eWXX2bXrl1kZmZyxRVXcNddd7WZGTl9+nSeeuop5s6dy0033dTzC+5vaL4Gwb1dorvQpMIdDsHt2isGDTvfEmGPDrLOgcLrxOkxHKh4MIVCoVAoGlm2bFlvLyFoDjoI/vhH+N3v2q6C5+SIQD/33J6pghsM8jhJSWLEtmmTzIKnpclaUlLAqMpaiq5gn2N69wAAXp9JREFUjBIzYWuaGJvV7myYB4+gkUi9EbInQ+bZUPwObHlO/JnWPwhbX4TCqyHznN53a49QevVZeeihh1iwYAEvvvgio0aN4ttvv+XKK68kPj6eG2+8sdl9Fy9ezFdffUVmZmYvrbYfoflEkNbtAEeZ3GZJCU+biKcWil6GbS9L/BiIYdqwG8RFPBy0igfLjwzHSIVCoVAoIgRN06ioqCAlJaXNYofP52PLli0ADBkyBH0vu4q1rIK//TZ88IG4j//jH7BggVTBp0yBI47omSq434jN6YTdu6GkRAzYcnOlOh5iPzrFQECnk1Zzc4JUvu1bJOknEqLHAtGbZMY761woXiyJRM4y+Ol+iQQecg1knhkev6Y+TK++iq5atYpJkyZx9tlnk5eXx9SpUzn99NNZvXp1s/uVlJRwww038Morr2AyqRaGLuPzSmV77zew92vZobKmQlRW6EW3zwPbX4flU2QexOuQqvORT8Lhfw+f6K6vlNkTU3xDLuEhSnQrFAqFQtHARx99xLhx47DZbGRkZGCz2Rg3bhwffvhhs/s5HA6GDRvGsGHDcDgcvbTatjnoILj9dmk//9OfYNQo8HikAj5jhrSgv/CCzGT3BFartJsPGiRu6GvWwMqVkgteVdUza1D0MwwWiBsOyUfLuXpdiZzjRhoGCwy+CCa8A8NvkqzyumL48V5Y+X8yF675uvStHQ4Xu/fsj7jXn+7Qq8L7uOOO45NPPmHjxo0AfP/996xcuZIzzzyz8T4+n4/LLruM2267jVGjRvXWUvs2Pq9Utvd9AxVfS3u5NU1MxkIdXaBpULYUVv4KNjwss9VRuTD2QTjmBUg+IrSP58dTJ/PjmibxYClHSwt7pMzGKBQKhULRyzz//POceeaZmEwmHnnkERYtWsQjjzyC0WjkrLPO4rnnnmt2//j4eOLjw+S/EgJsNpg0CV58EV55BX71KzE7Ky6Gxx+Hs84Sgf711+Dr2rl/UBiN0mqemysV9/XrYdUqWLcO9uzpmTUo+hmWZEg6AhIPlfP52p3gq+/tVbXGYIX8S0WAD7u+IS5tO3x/J3xxEez6pNMCfOVX65h6+W3EFpxKxthLiU3KYOoF5/PFF1+E+YcIP73as3D77bdTXV3NQQcdhMFgwOv18sADD3DJJZc03uehhx7CaDS2aj1vD5fLhcvlarxeXV0NgNvtxu12h/YHCCH+tYV0jT5Pk2maq0KMGsyp0h7iI+TvALp936Lf/Dj66vUAaOYkfAXX4MucLO0xXg3QQvqY8jPuEYFtK5A5blM0eAFveH/fYfmdKXoM9fvr+6jfYf9A/R57jj//+c/85je/YeHChc1unz59Otdccw333XdfY3a32Wxmz549jffp6PfjbXi/9fl673c4dCjcdhtcfz18/LGOxYv1/PSTno8/ho8/hqwsjcmTfZxzjo/k5PCvJzZWDn8c2fbtIsqzs+VjJMWRqf/BPoA1GwzxUFME9p24ddKp6vZE2m6OFXJ/A5nno9/xL/Q7XkFn3wrr/oAWMwzvkGvRUo5v14nw2Zff4ZY/zWF4poG/XWYhPw2KyuHFLz7m9NM/ZM6cOVx11VU9/DN1TDD/NzpN00KshDrPa6+9xm233cYjjzzCqFGjWLduHTfddBNz5szh8ssvZ82aNZx99tl89913jbPdeXl53HTTTe2aq917773Mnj271e2vvvoqUVEq7D0cxPm2MbL+n6R7vwPAg5VNpilsMZ2HVxeGKDKFQqFQKBRBc+GFF/LHP/6RsWPHtvrc2rVrefDBB/nXv/7V8wsLE0VFcSxdOphly3Koq5NRRYPBx9FHl3H66dsZM2ZPj8yCKxQDFaNmp9D9LgXu9zAhLeP79YX8bLqYcsNh/SIKoK6ujl//+tdUVVURFxfX4X17VXjn5ORw++23N4uruP/++3n55Zf5+eefmTdvHjfffHMzQw+v14terycnJ4dt27a1+p5tVbxzcnKoqKg44JPRm7jdbpYuXcppp53W9Tl2n1uqv/bt0uJtMIMpMXxmDI4yDFueRLdrCTo0NJ0BX9b5+AqulkiEcOGuBfc++dli8sGa0SvxYCH5nSl6DfX76/uo32H/QP0ee46JEydy6qmnctttt7X63MMPP8zSpUtZunRp0N932zY369cvJSPjNPQRGCfkcDSvgvvxV8HPPttHSkrPrMXng+pqcUS32SAzU/LAExJ6T4Oo/8G+h9tZw9JPV3DaaDCZjGBOiezxyvpK9DteQb/jX+h8TgB88aPxFVyHlnQk6HT8Zvqf+OXHL/jyHm+bG2I+Hxz7ZyMHHX42L/7znz38A7RPdXU1KSkpnRLevdpqXldX18ol02Aw4Gtogb7ssss49dRTm31+4sSJXHbZZVx55ZVtfk+LxYLF0toozGQy9YkXky6t0+cW07TabRLbZbBCzKDwCe76SnEs3P4v0BraKzJOQzd0BoboHMImgRvjwSyQFDnxYH3lb0vRNur31/dRv8P+gfo9hod9AQ5jf/3rX7n44otxu91MnjyZtLQ0ysvLWbx4Mf/85z9ZtGhR4+/A5XJx3XXXAfDUU0+1eW7lx9Dwxq/XmyJSeEdHyyz4pEkS/7V4Mfz3v1BSouOJJww8+aSBE04QU7ajjgqvI7pe3zyOrKhInNkjIY5M/Q/2JWIBMKUejslRBK4SSSgyRvfyutrBmAQH3QD5l0DRP2HHv9FX/Yh+7fWQeBiu3Kv497tLefRiH5b2/v/08Juj4dZFr/Psc89hs0VGV20w/zO9KrzPPfdcHnjgAXJzcxk1ahRr165t1rufnJxMcotBHJPJREZGBsOHD++NJUcW3npw7gJ7Ebj2Sf5fVGb4rPu9Ttj+mohuj11uSzoCht8gjuXhQvPKjLrPo+LBFAqFQqEIgpZxYZqmMXv2bP785z83uw3E9Nbr9QLg8Xh48cUXAXjiiSc6FN59iaFD4fe/hxtvFBf0xYvhhx/g00/lyMpqygUPdxW8ZRxZaakI8txcEeIRoisUkYw1HaJSRQsERo9FaoyXJQkOugnyLpUIsp1vwf7vsOz/jg9uA9sBvA8K0sDr9VFdXR0xwjsYelV4/+Mf/+BPf/oTM2bMoLy8nMzMTK677jruvvvu3lxW5ON1NQjubdJSboyC6Kzw/ZNpXih5HzY9Ba5yuS12qGRxpxwb3t6o+kpwV4ElTSLIrGmR3UqjUCgUCkUE8dxzz7WZ030gTCYTDz/8cOPlztB7w4vBY7WKuD73XNi8Gd56y18FhyeegCefhAkTpAp+9NHhrYL748g8HqislDiyuDipgGdkQAQbyysiAYMF4g+SinfNJqgtFoFriu3tlbWPNQVG3gYFv4Etz6EVv8Npoz0H/LKt5WAw6CN6fLgjelV4x8bGMm/ePObNm9fpr2lrrnvA4HU2tZTX7wNjDERlh0+IahrsWQEbHwf7VrnNmgFDfwuZZ4ZXAHscIvKNsRIPFpUtM+sKhUKhUCg6zRVXXNGlrzObzW3Ogrd9X/lYWip78f5Kbm+1TAdLYWFTFfzjj0WE//ADfPaZHIMGaUyZouO888JbBffHkSUnyxz4+vWwdauI8qwsuV2ZwSnaxZoC5njxerJvlsKVNSN8o6ehwJoOo/6ILv9yPn7+Ok7MK8PYTh3R54OnPzcyZfKkPlnthl4W3opO4nVCXWmD4K6UHayonPAK3/0/wMZ/wP61ct0UDwVXQu6vZGctXPg84CyXny1mqJinmWLC93gKhUKhUCi6RXq6fDziCKiqkrbp3bvB64WoKBHh1t63ZDkgViucc44cmzdLG/q773ooKzMyfz489VTPVMF1Oqlyx8dDXR3s2CFxZP458LS0yIojU0QQehPEFYI1Gao3in4wx0X+iGZUJtbD72PE1dfwygw4sqB5Q63PBze9BBuKvSxcNKv31tlNlPCOZDwOcPgFd5X840SHWXDbt8GmJ2D3Z3Jdb4HBF0PB5eFtWdE0qN8LnjqwZULMELAk94uYAYVCoVAo+ho+n4+ysjIABg0a1MoMty3S0yWnevhwEeCVlVBWJpfLy0UsxsSIGI/0ym1hoeSCb9w4ibVrk4mO/gO1taMaq+CZmWLWdt55kJoavnVERcnhdsO+fbBrlwjywYPl+Y5RtQlFW5gTIelwqShXb4TanWBLB33k7tiMP2Yst9x6O8fc9iBnjdXzt1/7GJQAz30ule4NxV7mz5/PuHHjenupXUYJ70jEU9dQ4d4OnmowxUF0bnhFqLMCtiyE4ndkphs9ZJ8LhdfKP204cdtFdJuTIGmkCO9eiAdTKBQKhUIhOBwOsrOzAbDb7URHd94t2WiUtujkZCgogJqaJvG9dy/s3983WtLXrl3B2rX/BS6jtvZgZs9ew4YNh/Gf/0hb/YIFsHChVMGnTJEquCFMpy8mkwhtn0+eyx9+EEGemSlt6ImJqlahaIHeCDF5Mu9dvQnqdoovlDkpYv9Ypl85ldEjC5m34FVG3b4Mk96H26dnyuRJLFw0q0+LblDCO/Ko2QKuneCpkfbuqJzw/nN47FD0Emx7RVraAdImwNCZEDskfI8LzePB4kZKPJixb85sKBQKhULR3zCGQBHrdGIU5jcLczhEOO7b19SS7vOJg3ektaQ/+eRsDIYxeL3PYzCs4733/sCTTy7l+uvhk09kFvz77wNnwZtiy8JVBdfrRWQnJkoc2dat0obu7zZITY3cjQxFL2GKg6RDxaC4eqMIcGtaRETytsW4o8cy7uixOOzVVO8vJS7/dGxxYWwr6UHUv2ak4K2Xj1XrwZYgsVnhFNw+N+x4E7Y8A+5KuS1hjDiVJx0avseFpngwr1s2FmILIn/2RKFQKBSKfk5NTQ2xsTJWFh0djdvtDvlj2GxyZGTAsGFNLem7d0dWS/ratStYs+YT4E3AgNd7D99+O5V161Yydux4zj4bzj4btmyBt9+G//xH2uqffBKefhrGj5dZ8GOOCV8VvK04soQEyMtTcWSKFuj0Mq5qSWpwPt8hbeeWlIitfttsFmzGxH71hxzhEzYDCK3BQt+aKo6E4fon0HxQugRWTIWfHxXRHT0YDn0Ejn42/KK7vhLqSsAYBylHQdJYJboVCoVCoegBrrnmmnY/t2/fPk4++eQeXE1TS/qQIXDssSJWjzhCKsf19SIki4tFmHsOnDQUUvzVbpjccMsUDIbRPPnk7Gb3GzIEbrlFosj+/GcYO1ZM5T7/HH73O6l+P/OMbCiEC38cWUaGiPA1a+CLL+Dnn2UzQ6FoxBgNCYdA0hFgsIkA99T19qoGDKriPZCo+Fqcyqt/luuWZCi8DrLOC3/UgNcpbuXGGPmHV/FgCoVCoVD0KO+++y6zZs1i7ty5zW7fs2cPp5xyCj6fr5dWJvWG2Fg5cnJEQFZWNrWkl5eL+O4Jl/Tm1W5/jUrfquodiNUKZ50lx9at4oj+n/+IGVpgFXzKFNlkCEcVvGUc2YYNUFQkgjwrSz4X6aZ2ih5Ap4OoTDFgs2+F2iJwV0vxT6c8lsKJEt4Dgeqf4Zd/wN6v5bohWgLrB/86/DPVmlfmuDUfxBTIEU53dIVCoVAoFG2yZMkSTjnlFGJiYrjvvvsAKC0t5eSTT8Zms/Hpp5823tflcnHzzTcDMGfOHCyWMEaJtoHVKoLR35JeXS1CfNeuppZ0k0mEeqhb0ptmuye3+ExT1fvJJ5e2+/UFBVIFv/56+PRTmQVfu1aq4J9/LvPYkydLNTwtLXTr9hMYR+ZwwM6dcqSmqjgyRQBGG8SPFMFdvRFqiyWGzKis8sOFEt79mboS2LQAypbIdZ1RcriHXCW7XOGmvhLcVWDNkHgwa1rEzpEoFAqFQtHfOeyww3j//fc544wziI2N5cILL+Tkk08mOTmZjz76iISEhMb7ejwe5s+fD8DDDz/c48I7EKMRkpLkyM8XU7FAl/TKSrlfdLQI8e6Yi7Vd7fbTcdW7JRYLnHmmHEVFTVXw3bslEzxwFjxcVXCbTardbre4yas4MkUzdDo5PzfFS3yxfQvUV8tt4e6GHYCoZ7Q/Ul8JW56FHf9umh0fdAYMnS4t3uGmWVv5WDFz0JvC/7gKhUKhUCg6ZNy4cSxevJhzzz2Xhx9+mJEjR/Lf//6XmBYKzGQycc899zRejhQCW9Kzs6UlvapKRGVgS7rfJT1YX6Ynn5yNTpeMplmAD9q4hxWdLvmAVe+W5OfDzTfDzJlSBV+8GL77DpYvlyM9vckRPT0MKa4mk1S6/XFk338vGxWZmeGpuiv6GAYLxA0Xs7XqjeAoAVOC+E4pQoYS3v0JjwO2vwpF/wRPrdyWfBQMuxHiDwr/46u2coVCoVAoIoq33nqrzdsvuugi3n//faZNm8ZHH33UePv5558PgNls5t577+2JJXYLq1WO9HQoLJSW9KoqqexWVsKePSI6Y2JEaHbUku71evnppy/RtDrgnHbvp2nw44+r8Hq9GIIsUwdWwbdtEwH+/vuyabBwoRixjRsnVfDjjgt9FbytOLJt2+RzZWXyPPZic4Oit7EkQ/IRYrpWs1naz23pqoAWIpTw7g/4PFDyHmx+SmK6QHatht0AKcf0zBr8beWWdIgtVG3lCoVCoVBEAFOnTu3w85dffnnjZZ1Oh9frDfeSwkZgS3peXlNLekWFHCUlcmoSHS1CvGUh32Aw8OGHZdTV1RzwsaKiYoMW3S3Jy4NZs2DGDMkBf+stqYKvWCFHejqcd55UwTMyuvVQbeKPI3M4pGX/u++kkyArS6rgCQnKjG1AojdB7BAR4TWbZHTVFNMzY6r9HCW8+zKaBuWfw8bHZS4DwJYJQ2fAoNMlsy/cqLZyhUKhUCgilqKioi59naZpVDVkUcXHx6PrY5vpB2pJr6iQueeWLekxMXHExMT16FotFjjjDDm2bZNc8Pfek3U+/TQ8+6xUwadMkSp4d2bY23t8kEgyu11iyDZvFnf07GxxQ+9HUcqKzmJOgMTDpJhWvRHsO6T6bVAtEV1FCe++yv518MtjUPmDXDfFw5BrIPcC0PeAVWWztvJ8MU9TbeUKhUKhUEQUgwcP7tLX1dXVkZgoFS673U50dHQol9XjBLakDx0qItzfkl5VJS3pRqMI9QO1pIeTvDy46Sapgvtnwdes6ZkquF4vVe6EBHC5pFW/rEyeE39OeGJieEzgFBGK3gDRg8GcBNWboW4HGK1gTladrV1ACe++hn2rVLjLl8t1vQXyLoH830gbSE+g2soVCoVCoehzbN++nerqakaPHg1IZNijjz7Khg0bOPXUU7niiit6d4E9hMHQvCW9tlZEpr8lvbRU7tdeS3pPYDY3r4K/807rKvhxx0kVfNy48FTB09KkudJuhy1bZB48KampCq4c0QcQplhIOgRsDdFjdTvl/N9g7e2V9SmU8O4rOMtlhrv4PcAnAfdZ50HhtZK/1xN4nVLlNkartnKFQqFQKPoY06ZNY+zYsTz88MMA/OEPf2D+/PmMGTOG119/nbq6OmbMmAFAVFQU9fX1ABhDreoiCJ2uadY5O1sqvVVVsG9f85b0qCiIi+ud/Ou8PPjd7+C3v5VZ8MWL4dtvYeVKOVJTpQI+eXLoq+CBLftutzw3330nmxLp6VIJT04OvfBXRCA6vaQjmZMajNe2S+SYJaVnxlv7AerfJNJx14hL+bZXweeS29JPgqEzISavZ9bQ2FbulcdUbeUKhUKhUPQ51q1bxw033ABITveLL77IQw89xKxZs/jLX/7CggULGoW3TqeLqBixnsJf6U1Lk5b06mqphpeUiAGZxyMiPD6+58Wm2QwTJ8qxfXvTLPiePeKGHlgFHz8+9OszmaTSnZIiXQI7d8o6EhJk0yI1VQS6aoLs5xijIGF0w+z3L1L9tqRIYU7RIUp4Ryq+esnh3vKctHUDJBwCw2+ExEN6bh2qrVyhUCgUin5BTU0N8fGSy/v1119TXV3NRRddBMD48eN54IEHenN5EYfB0BS9NXiwCPB9+0SE794tmdixsVIt72kRPnhwUxV82TKpgn/zDXzxhRz+KvikSVKVDjXR0XJ4PLI58cMPMkOflibZ4MnJvdMdoOghdDqwZYgBW81WqC0Cd3WDTlAmAO2hhHeE4HQ65KPDiWnvMti4AJxl8snofBh+PaRO6DnRq9rKFQqFQqHoV2RnZ/PVV18xYcIE3nrrLUaOHMmgBlW2f/9+oqKiGu9bX1/PnXfeCcADDzyAeYCrKL2+aS48P1/c0ffulXnwXbvkPn4R3pPmY2YznH66HO1VwY89VnLBw1EFD4xwczjEjG3nziY3eX8smarZ9FMMVkgYKWOv1Rsl99uSpDpj20EJ715m5cqVzJs7hw8/+pAPX7iNon/fx5gcn3zSkgpDr4PMc2SGoidQbeUKhUKhUPRLrr76au666y7+/e9/s3btWubOndv4ua+++ooRI0Y0Xne73Tz66KMA3HvvvQNeeAdiMDS1XBcUiAivqBDRWVYmIjMurufd0QOr4J9/LlXw1ath1So5UlKaquCZmaF/fJtNDp9PquDr17eOJbMqL67+iTVVEpZqt4F9S0P1O73n9EsfQT0bvciCBQuYOXMmp4/Rs/4vGjmu2ZAD1Q7467swZMJvuOakyT23INVWrlAoFApFv+X2228nMzOTb775hhkzZjRzMd+/fz/XXHNN43WTycStt97aeFnRNiZT00x4YaG0ou/ZI63oJSUi0v0ivKdOqcxmOO00OXbuFAH+3nuyOfDss/Dcc1IFnzIFjj8+9JsDgbFkTqc8J/5YssxMMWVLTOy9yDbF/7d35+ExnusfwL+zZSb7SgRJ0Kg1IjmoWquo1lK0Squ19ughDqWOLtpq/bS2HtRpe7SqB13oOVpK0aq2tNRepEStRRJBQmRfZ+b5/fF0JhmChEzeeSffz3W9l8nMO8md3JmY+72fxUl0HoDf3XK+d84JoCAVMPjJ4egEgIW3Ynbs2IHx48djwgMCC5+yQKMFLH+mw8doRl4h8MzU+WjWvBk63tPaucFwWDkREVGNMHz4cAwfPvy6+99//32Hjz08PPDWW29VV1huwcNDripep45cmM22Mnp6urzt4SGL8DIj+p0uPByYOLG0C75mzfVd8H79tGjf3tMpXXDb/ulCADk5wMmTcmuy4GCgXj359VW+RTxdyxgEGNoAeUlAzkk5/NwzlLUFWHgr5u2FC9Csvg4LnzJDqwXM8MCPnu+gW8EkGLRmvD0M+OGoDm8vXum8wpvDyomIiGqMpKSkW54TERFRDZG4P5NJdnfr1gXy82XhffGinBd++bJcPd3fv/qGXhsMQI8e8khOLp0LfvkysGyZDsuX98Q99wg88gjQpUvVzwW3Db/385PbkmVmyosSXl7yQkVYmJwnzm3J3IRWD/g2AozBcuux/GTZ4PMIrNGjafnrrYCCggJ8tW4d/vmE1T7MRkCHAm2o/RytFhhznwX/WLUNBQWF8PSs4r/MHFZORERUozRo0ACaW/xfb7FYAABCCJjNZgByH+9bPY9uzMtLHvXrA7m5sghPTZVzw23Fp5+fLMarQ3g4MGECMHasrQtuxd69WuzercHu3bIb/fDDcl/wevWq/usbDHLVdSHktmRnz8ojIEDGZtuWjNyAhz8Q2PrPxddOygLcFAroqumX3cWw8FZAdnY2LBYr7gq9+XmNagMWixXZOXlVV3jbhpXrvDisnIiIqAZZu3btdfddvXoVmzdvxu7duzFnzhz7/fn5+fDx8QEA5ObmwpvjgauEj488wsPl0OuyRXhRkRx27e8vi1Nns3XB77/fgl9//QG7d9+Pr7/W4coVYNkyYPly4J574NQuuO3nYTYDWVlAQoJcoC00VHbBg4Or52dBTqTVAd4RgEcQkHsKyD0nV0M3Bte4ph8LbwX4+flBp9Pi9CXrTc/7Iw3Q6bTw862C/+w4rJyIiKhG69+/f7n3jxw5Es899xx++uknDBkypJqjqpnKDr2OiJCrgNu2J0tPBywWWYT7+VXP8OuwsHyMH2/F2LE6/PyzXJBt9+7Sw9YF799fdu6rml4vv0ZwsByan5ICJCXJ779+fdkF9/evcXWaezH4AAGtAGNtufhaXpIccav3VDqyasP1BBXg6emJAf3748Of9LDeoPa2WoEPt+kwsPd9d97tLs4E8lPkMv/B9wABMSy6iYiIyK537974/PPP7R97eXnh6tWr1+3vTVXPtgr4XXcBHToAHTsCLVrIxdguXpRFaGamLMadzWAAuncH3n1XzgMfNUoWw7Yu+IABwPjxwA8/yC61M3h5ybnxYWHyez5yBPjlF2DfPrlSfFHR7X3ekpKSqg2UKk+jBbzqynrEtzFQfBUovASImzcj3QULb4VMmvwcfk+xYPKnuK74tlqBSZ8Av5+3YNK4obf/RSyFQF4yYLXIYju4nVxVkJcLiYiIqIydO3fCVGalL41Gg4CAAAQEBHB+dzXS6eQiY40bywK8Y0egSRP51u3CBVmEZ2Vd/97RGerXl0X2xo3AvHlA+/by/j17gBdeAPr0kQV6Sopzvr5OJ7cdi4iQFybS0+WK7Dt2AMeOyWH6Ff057Ny5E7Vq1cauXbucEyxVjt4TCGgpaxO9r5z7bc5VOiqn41BzhXTq1An//ve/ER8fj++P6vBMd6DBAODfW4Al3+vw+3kL/v3Wi7e3orl9WLmVw8qJiIgIADBx4sTr7isuLsbvv/+OHTt22PftJteg18vttkJCZDf86lVZfF68KDu/Wq0ciu3j49yeil4P3H+/PM6fl53w9etlF3z5cnm0ayfngnft6pw52SaTXP3capVz448dA06dctyW7GYDM15+eTqysjLx8svT8eOPW6o+QKo8jUY2BD0CgNwzQO5poDj7zyahTunonIKFt4LGjh2L6OhovL1wIV754lt8OgB45QstHuzWFUuWDL29ors4EyjJBoy15BAOrlZOREREAL7++uvr7jOZTKhfvz7+/e9/469//av9/uLiYsyaNQsAMG3aNHh4eFRbnHQ9gwGoXVseUVGy25uWJo/kZPm4bY9wZ77tq1dPdsH/9jdg+3Y5F3zXLtmJ3rtXduv79ZND0sPDq/7ra7Vyrre/P1BcLIfgX7wo58OHhcniPChIdstttm/fjm3bfgAwDFu3foIdO3agU6dOVR8c3R6dEfBvChhDSvf9NgYCWvdb+ZyFt8I6duyIjh07IufqRfz48x6k/rYOvv4Blf9EDquVtwK8wgEd/5MkIiIi6cyZMxU+t6SkBDNmzAAATJ06lYW3CzEaZZEZFgYUFMgi/NIl2Q2/ckXODff3l6uDO4teD3TrJo/z54F16+Rx5QqwYoU8nN0F9/CQFyKEkNu0/fGHPIKCZNEfEiJHA0yfPgM6XStYLMug0x3C9Okz2PV2RaYQuf1Y7jm5+nnRVUBfTRvdVxMW3i7CZPL8899K/sfGYeVERERUxfR6PeLj4+23yTV5esoudL16ck/sjAzZAb5yRXbDPT1lJ9zkxPqlXj0gPh545hk5/3rNGscueGCg7IIPHOicLrhGI/f99vWVC75lZgIHDsgu+Pnztm73lwB0sFhew9atg9j1dlVaA+AXBZiC5b7fbjbvm39J1YzDyomIiOgmPv7440qdP3z4cACA0WjEe++954yQyEm8veVRv77sAJfdI/zSpdLtyZw1eEGvB+67Tx6pqaVd8MuXgY8/lkfbtrILft99zumCl50Xn5cHvP32DGi1rWC1DvjzjIHQ6aLZ9XZ1HoFAUJysdfRVsK2yi2DhrUYcVk5EREQVMHLkSPuq5EKIm56r0WjshTepV9kOsG2P8IwMOSQ8I0POjbYV4c4ofgG5Hdi4ccCYMY5d8H375BEYCPTtK7vgERHOieHEie04fNjW7bZt5KS1d703bdqBXr06OcwHJxei1cvh526EhbeacFg5ERERVYLRaITBYMDAgQMxdOhQtLftCUU1gkZTuhhZZKTciuzKFVmEp6fLfbK9ndhQLNsFv3ChtAueng588ok82rQp7YJXZTf+/fdtc7sHXPPIQGi10XjxxRnw9t6CunXlhYCAABkvkbPw10stirPkcAtTbQ4rJyIiogpJT0/H2rVrsWrVKvTr1w/h4eEYOnQonnjiCTRv3vyGz8vLy0NAQAAAIDMzE97OrM6oWmi1ssAMDAQaNpRzoS9flsPCAflvYKDzCvGwMGDsWOCvfwV++UV2wXfuBPbvl0dAQOmK6JGRd/a1Dh7cjl9/vbbbbaOF1foaDh8ehAMHduDq1U7QaOQIgLAwuUVZQIDzRgNQzXXtbyK5GkshkJcMWM1AYIzcaN4zlEU3ERER3ZKPjw+GDRuGTZs2ITU1FVOmTMFPP/2E6OhoxMTEYO7cuUhOTi73uWazGWazuZojpuqg08kCs0kTwDYIIjxcrpKelCS74haLc762Xi9XOl+0CPj6azkcvXZteSHgk0+ARx+VBfrmzXJY/O14//0Z0GiCARgBfFPOYYJGE4yVK2cgPLx0j/Djx+XFgJ9/BhIT5dz4oqKq+b6J2PF2VdcNK28EGPyUjoqIiIhUKiQkBPHx8YiPj0dKSgoWLlyIV155BXv27MGaNWsczvX09ERKSor9Nrkv2/Dq6GigsFCuhp6SIoeG27rkzvoVqFNH7gn+9NOy4L22C+7vX9oFb9CgYp/TYrHgyJFdECIfQN8bnicEcPjwTlgsFuj1OgQEyE63xQLk5ACnTsnDx0deGAgJkT8LZ64QT+6NhbcrchhWHgWY2OEmIiKiO5eVlYU1a9Zg1apV2Lp1Kxo1aoR+/fpdd55Wq0W9evUUiJCUVHZRNttccNse4X5+8tA6YbysXg906SKPixdL54KnpQGffiqPuDg5F/z++28+F1yn02Hz5gvIz8+55df18vKF7prV1XQ62Itwq7V0j3BbEV6rlizEAwIAL687+raphmHh7WoKLgEmPzmsnKuVExER0R0qKCjA+vXrsWrVKnz77beoXbs2hgwZgjlz5iAuLk7p8MgFGQyyGx0aKldFT0sDkpNlIW4wyM6v0eicr122C75rl+yC//KL3Jv7wAHZBbetiH6jLriPjx98fO58pKhWW3rBwWoF8vPlz+HMGVl0ly3CfXzu+MuRm2Ph7TL+vHzo2wgIiOKwciIiIrpjQ4cOxddffw0vLy8MGjQIW7ZsQefOnW/5vOLiYixatAgA8Oyzz8LDWZs/k0sruyp6RIRcjC0lRf5bUiLv9/V1zsBMvR7o3FkeFy8C69fLLvilS8Bnn8nD1gXv1s15FwJstFpZXPv4yGHqeXlyOP7Zs3JBusBAedEgMFCew8GqdC0W3q5C/+eEEf+WgIH/uREREdGd+/zzz+Hr64u//OUvSE5OxltvvYW33nqr3HM1Gg3WrVsHACgpKcHzzz8PAIiPj2fhTTAagXr15B7dV6/KYjg1VXaATSZZcDprJfA6dYBnnnGcC35tF7xPH1mEV3Qu+J3QaByL8IICORz//PnSn0VYmOyE+/mxCCeJhber4SuTiIiIqkiXLl2g0WhQUFBQqefp9XqMGDHCfpvIRqMBgoLk0bCh7H4nJ8vh6ELIYtPb2zlvaXW60i74pUuyC/7VV/L2ypXyiIuTw9Dvv9/5XXBAfp9eXqXzvQsL5YWJ1FT59W1FeGCg8+bIkzrwLykRERGRm9q2bdttPc9oNGL58uVVGgu5H09PuQ1ZvXpARoYcep2aKhdm8/aWRbizrtuEhsqtyEaPLp0LvmNHaRf8n/+UXfCBA+UFgupiMpWufF5YKFdIv3RJLghn2ys8KEh26a9Z143cHAtvIiIiIiK6bVqt3G4rJARo1EgOu05OlsPRtVrnrgCu0wGdOskjLa20C37xYmkXPDa2tAtenduBlS3Ci4vlQnVHjsiY/fzksP3AQOdeoCDXwRQTEREREVGV8PaWR/36svOdmio7vpcvy4XY/Pyc1+mtXRv461+BUaNkF3ztWtkFP3hQHmW74I0aOSeGG/HwkBcmALkwXU4OkJgoL0z4+spOeHCwLMKdNVeelMXCm4iIiIgc5OXl2ffxPn/+PLy9vRWOiNRGr5fDwctuSZaSIgtxvV52ep3Vfb5ZF3zVKnm0bi0L8O7dq7cLDsjC2jZP3myWe4UfPy4f8/GRi8mFhMgivDrmqVP1YOFNRERERNfJyspSOgRyE7a9sCMjS7ckS0uTw69tjzlr0bGyXfDdu2UXfPt24NAhecyfL7vgAwYAd93lnBhuRq+XBXZAAGCxyE74qVPAyZOyE167tizCnXmhgqoHC28iIiIicuDp6YkTJ07YbxNVBYNBDqmuUwfIypJD0FNS5GFbAdxZO9fpdEDHjvJITy/tgl+4UNoFj4mRXfAePZQpcnW60iLcapWd8DNngNOn5fD9WrVkIe7jU/2x0Z1j4U1EREREDrRaLRo3bqx0GOSmNJrSArNBA1kIp6TIbrjFIlf89vFx3i67tWrJPcFHjgT27JFd8J9/BhIS5GHrgg8cqEwXHJAjAGyjAaxWIC9PLlh35oxcTR6Q+4YHBcnOOHckdn0svImIiIhqiOPHj+PLL79ESkoKCgsLHR7TaDT46KOPFIqMaiqjUS7EVreu3P/64kU5Dzwpyflbkul0QIcO8rh8ubQLnpoKfP65PFq1Ah55RLkuOFC6AJuvr9wrPTcXKCqSC8YZjfJnFBoq//X35wrproppISIiIqoBPvnkE4waNQomkwmRkZHwuGZMr6ZMy6ykpARLliwBADzzzDMwcJllcjKtVq7qHRws9922bUl26ZIsNgMCnDvEOiRE7glu64KvWSO74L/9Jo/584HevWUXPCrKeXHcikYjL0hkZckLFsXFcl54WlppgR4aWrpXOGeKuA4W3kREREQ1wMyZMzFo0CD85z//gdctNlUuLi7G3//+dwDAyJEjWXhTtfLykgux1a8PZGTIDvTFi3J7Mh8f53Z1tVrg3nvlcfky8PXXsgt+/jzw3//Ko1UrWYD37Kn8gmdl9wq3rZB+8qS8WOHtLS9k1Kolf2Yckq4sFt5ERERENUBqaioWL158y6IbAHQ6HQYNGmS/TaQEnU4WjbVqybnWaWmyC37xoiyQAwOd29ENCZGroY8YAezdK7vgP/10fRf8kUeU7YLblF0h3WoF8vPl4nHnzsni3N+fQ9KVxB83ERERUQ3QpUsXHDlyBN27d7/luSaTCatXr66GqIgqxsdHHhERshN9/rwsxNPTnb8lmVYLtG8vj2u74P/7nzyio2UB7gpdcEDGbPuZAUBh4Y2HpAcEuEbM7o6FNxEREVENMGvWLDz11FMwmUzo2bMnAgICrjsnKCio+gMjqgS9Xm5HFhoKZGeXdsHPn5fblTm7iLy2C752LbBtG3D4sDzmzwceekgW4a60MQCHpCuPhTcRERFRDRAXFwcAGDdunMNCamVZLJbqDInotmk0skj095fzwctuSVZSUtoFd1YBWbYLfuWK7IKvXSsvAKxeLY+WLUu74K60yNmNhqSfPSvj5JB05+CPkYiIiKgG+M9//nPDgvta+fn59n28T548WaF54URK8fAA6tWTW5JlZsqV0FNS5JZknp5yLrgz1wcMDparoQ8fDuzbJwvwrVuBI0fkUXZF9Lvvdl4ct+NGQ9IvXZIFt48Ph6RXFRbeRERERDXAyJEjK3yuEAKpqan220RqoNHIIjswEGjQoLQLnp4uO7vO3pJMqwXuuUceti74V1/JGMp2wQcOBB54wLW64DYVHZJu+1lySHrFsfAmIiIiqkGuXr2KvXv3IiMjA0FBQWjXrh0CAwMdzjGZTDh48KD9NpHamExAeLjshGdkyKHUqanytr+/c4ehA45d8P37r++CL1gg54IPHAg0aeK8OO5ERYak16kjH/fz45D0W+GPh4iIiKgGEELghRdewDvvvIOioiL7/UajERMnTsTcuXPt9+l0OrRu3VqBKImqllYrF0QLCZFd8NRUOQQ9KUkWi/7+zlsN3fb127WTR0ZG6VzwlBTgiy/k0by5nAv+wANyD3NXxCHpd46FNxEREVENMGvWLCxcuBDPP/88hgwZgtDQUFy6dAn//e9/MW/ePAQEBOCll15SOkwip/H1ld3l8HC5F/jZs7IA9vKSxaKzO7ZBQXI19GHDgF9/lfuCb90KHD0qj4ULgQcflF3wpk2dG8udutGQdED+PDkk/XosvImIiIhqgKVLl+LVV1/F9OnT7feFhoaiVatWMBqNWLJkib3wLikpwWeffQYAePLJJ2Fw5spURNXMywto1EgOQ790CTh3Tg6hNhhkwejsX3etFmjbVh4ZGcCGDbILnpwMfPmlPNTQBbe50ZD0c+dkcc4h6VIN/baJiIiIapYLFy6gQ4cO5T527733YtasWfaPi4uLMWrUKADAY489xsKb3JLRCEREyNXQ09Lk8PO0NNmdDQqqnuHSQUFyHvhTT5XfBV+wQHbBH3nE9bvgQMWHpAcHy4K8Jg1JZ+FNREREVAM0aNAAGzduRI8ePa57bNOmTWjQoIH9Y51Oh969e9tvE7kzvV4W33XqyH3Ak5PlUHSzWa6Q7u3t/BjKdsGvXi3tgiclyWJ8zRrZBR84ECjnJeyybjQk/eRJ2cm3zb+vCUPSWXgTERER1QCTJ0/GuHHjkJ6ejkGDBiE0NBRpaWlYvXo1Vq1ahcWLF9vPNZlM2Lhxo4LRElU/rRaoXVvOTb56Vc7/Tk2VW4MFBMg54tVRGAYGynngN+qCL1yoR6dOMXjqKVmMq0V5Q9LPn5dz7WvCkHQ3+3aIiIiIqDx/+9vfUFxcjJkzZ2LlypXQaDQQQqBWrVpYtGgRnnnmGaVDJHIJtqHmQUHXr4Ru24rMmSuhl42jTRt5XL0KbNwoi/CkJA2++64BvvsOaNZMdsF79aqeznxVqciQ9Dp1gMaN3acAd5Nvg4iIiIhuZcKECRg/fjyOHTuGq1evIigoCE2aNIG2OqoIIhXy85NHeSuhBwYC1TUTIzBQdsCffBLYv9+MlSsvYvfuevj9dw1+/x14+21ZfD/yiCzG1ebaIemZmcCZM/LnbivO1Y6FNxEREVENotVq0fwW41Pz8/MRExMDAEhISICXqy+rTORk3t7AXXcB9euXFuDnz8sF2oKDq68rq9EAf/mLQFjYr/DyCsWmTQasXStXEF+7Vh5Nm8ou+IMPqqsLbqPXy2H9mZlKR1K1WHgTERERuakFCxZU+FyNRoPJkycDAIQQOHXqlP02EUlGIxAZ6bgS+sWLcuh0cLB8vLoEBJR2wQ8ckEX3Dz8Ax44Bs2fLLrhtX/Bmzdx74TI1YOFNRERE5Kb+8Y9/VPjcsoW3yWTCjh077LeJyJHBIPcBt62EnpQk5ydbLHJueHUOEpFdcHn84x+lc8HLdsGbNCntgrvL0G21YeFNRERE5KasVuttPU+n06Fjx45VHA2R+9Hp5L7UtWsDGRlyK7ILFxxXQq9OAQGyAz50KHDwYGkX/PhxYM4cYNEiORd84EC5Ijq74NWHhTcREREREdEd0GjkUPPgYKBhQzn/OzlZFuP+/vKoziJXowHi4uQxZYrsgq9dK+emf/WVPO6+Wy7Gxi549eASlkRERERuat68ebh48aLDfTt37kR+fr7DfWfOnHHYTsxsNmP16tVYvXo1zGZztcRK5C78/WU3uWNHoFUreV9SkuyCWyzVH4+tC756NfDhh8BDDwEeHsCJE7IL/uCDwMyZwJEjAJd0cB4W3kRERERu6qWXXkJSUpL9Y4vFgs6dO+PYsWMO56WlpeGjjz6yf1xUVITBgwdj8ODBKCoqqrZ4idyJjw8QFSUL8Lg4ufDa+fNyUTYlrmdpNEBsrCyyN20CnntOducLC4F164CRI0sL9Nzc6o/P3XGoOREREZGbKm9F8oqsUq7VatG1a1f7bSK6fSYT0KCBXIzt0qXSldB1OrkQW3WuhG4TECDngT/xBJCQIBdj+/572QWfO1fOBX/gATkUvUULzgWvCiy8iYiIiMiBp6cntm3bpnQYRG7FYJD7gIeFAenppSuhW61ybrinZ/XHpNEArVvLY8oU2Qlfuxb44w9g/Xp5NG4sC/CHHuJc8Duh6CVMi8WCV199FQ0bNoSnpyfuuusuzJw50+FK7Ouvv46mTZvC29sbgYGB6NGjB/bs2aNg1ERERERERLdHp5PbkLVpA9x7LxARAWRny8XYlBzi7e8vO+D//S+wdCnQp4/sxp88KbvgvXoBM2YAhw9zLvjtULTjPXfuXCxevBgrVqxAixYtsH//fowaNQr+/v6YOHEiAODuu+/Gu+++i0aNGqGgoAALFy7EAw88gFOnTqFWrVpKhk9ERETk8jTljBEt7z4iql5aLRAS4rgSekpK6VZkfn7KDPEu2wV/7jngm2/kUPQ//gC+/loejRvLLckeeqj6t0xTK0UL7507d6J///7o06cPAKBBgwZYtWoV9u7daz9n6NChDs9ZsGABPvroI/z222/o3r17tcZLREREpDbdunW7bp52586dHe67dr/vgoIC3HvvvQCAXbt2wVOJMbBENYRGIwvtgADZ/b5wQQ5DT0qSRW1AgCzSleDvDzz+ODBkCPDbb6VzwU+eBObNK50LPnAgEB3NueA3o2jh3aFDByxZsgQnTpzA3XffjYSEBOzYsQMLFiwo9/zi4mIsWbIE/v7+iImJKfecoqIih9U3s7OzAQAlJSUoKSmp+m+iithic+UYyRFzpm7Mn/oxh+6BeXSuV155pVLn2/JQVFSEhIQE+229/sZvGZlDdWP+XIvJJLvfYWFy9fOkJNkFN5lkAa7XA1arzJXt3+oSHS2PyZOBb77RYu1aLf74Q2PvgkdFCQwYYMVDD1nvuAtutcrh7GYz4Mq/mpV53WhERZa2dBKr1Ypp06Zh3rx50Ol0sFgsePPNN/HSSy85nLdhwwY8/vjjyM/PR1hYGL766iu0bdu23M/5+uuvY8aMGdfdv3LlSnh5eTnl+yAiIiJyJxaLBYcPHwYAREdHQ6fTKRwREbkaIYDjxwOxeXMD/PJLPRQXy78THh5mdOyYil69zqJJk6tu3QXPz8/H0KFDkZWVBT8/v5ueq2jh/fnnn2Pq1Kl466230KJFCxw6dAiTJk3CggULMGLECPt5eXl5uHDhAi5fvowPP/wQP/74I/bs2YPatWtf9znL63iHh4fj8uXLt/xhKKmkpARbtmxBz549YTAYlA6HKoA5UzfmT/2YQ/fAPKofc6huzJ86mM1y7ndyMpCWVgJgCwIDe8LT0zVylp0NfPut7IKfPl1aad91V2kXvDKlWFERkJUl90D39nZCwFUkOzsbISEhFSq8FR1qPnXqVLz44ot4/PHHAcgrqufOncPs2bMdCm9vb29ERUUhKioK7du3R+PGjfHRRx9d1xkHAKPRCGM5m+EZDAZV/DFRS5xUijlTN+ZP/ZhD98A8qh9zqG7Mn2uzbUVWt67cgmzvXiAry4DMTAOCg+VQdCUFBJTOBT98WG5J9t13wOnTGsyfr8O77+rQo4ecCx4Tc+u54FqtPEevl9+7q6rMa0bRwjs/P/+6xT50Ot11C3xcy2q1OnS1iYiIiKjqmM1mbN68GQDQq1evm87xJqLqY1sJHQDatpULsaWmyo54SIjyBbhGA7RqJY+yK6KfOgVs3CiPRo3kvuC9e6NSXXC1U/SvaL9+/fDmm28iIiICLVq0wMGDB7FgwQKMHj0agBxi/uabb+Lhhx9GWFgYLl++jPfeew/nz5/HY489pmToRERERG6rqKgIffv2BQDk5uay8CZyQcHBQGioXAk9Kam0AA8OBlxhIwJfX2DwYOCxx4AjR2QB/t13cluyf/4TeOcdoHt3WYRXpAuudor+FX3nnXfw6quvIj4+Hmlpaahbty7+9re/Yfr06QBk9/vYsWNYsWIFLl++jODgYLRt2xbbt29HixYtlAydiIiIyG1ptVq0adPGfpuIXJNGIwvtoCAgMlIW4OfPy/ngrlKAazSlK6JPmVLaBT95Eti0SR6NGslh6L17yy3M3JGihbevry/efvttvP322+U+bjKZsGbNmuoNioiIiKiG8/T0xL59+5QOg4gqSKORxXdgYGkH3FaABwUBrrK5k4+P7IAPGgQkJjp2wefPL+2C9+0rLyS4E44bIiIiIiIicgO2AvxGHXBXKcA1GqBlS3k89xzw7beyCD9xQnbEv/kGCA8H/vc/oH17paOtGiy8iYiIiIiI3ExgoDyuLcCDglxriy4fH9kBf/RR2QVfuxbYvBlIS5Pde3fBwpuIiIiIHBQUFKBHjx4AgO+//x6erjBRlIhuS0CAPCIi5D7gKSlARoYsyn18lI6uVNku+PjxwP797rXqOQtvIiIiInJgtVqxc+dO+20iUr/yCvCrV12vAAdkRz4mRukoqhYLbyIiIiJyYDQasXbtWvttInIf/v7yCA+XxbetAx4U5HoFuDth4U1EREREDvR6PQYMGKB0GETkRNcW4MnJLMCdiYU3ERERERFRDeXnBzRvLgvw5OTSAjwwEPD1VTo698HCm4iIiIgcWCwWbN++HQDQuXNn6HQ6hSMiImfz9S0twM+fB86dKy3A3WmRM6Ww8CYiIiIiB4WFhejWrRsAIDc3F96utPcQETmVry/QtClQv35pAZ6UJBdm8/WVq49T5bHwJiIiIiIHGo0GzZs3t98moprHxwdo0gSoV08W4ElJpQW4nx8L8Mpi4U1EREREDry8vJCYmKh0GETkAmwF+LUdcNvibCzAK4aFNxEREREREd2Utzdw992yAE9NBc6eZQFeGSy8iYiIiIiIqEK8vICoKKBuXVmAswNeMVqlAyAiIiIi11JQUICePXuiZ8+eKCgoUDocInJBtgK8QwcgJkbel5QEZGYCQigamktix5uIiIiIHFitVnz//ff220REN+LpCdx1V2kH3DYE3c9PLsTGDrjEwpuIiIiIHBiNRnz66af220REt2IrwOvVkwX4mTOyAPf1lQW4toaPtWbhTUREREQO9Ho9nnzySaXDICIVMpmARo1kB/ziReCPP4DkZBbgLLyJiIiIiIioSplMQIMGQFgYcOGCHIKekiJXRw8MrHkFOAtvIiIiInJgsVhw4MABAEBcXBx0Op3CERGRWhmNpQX4xYtyCHpysizAg4JqTgHOwpuIiIiIHBQWFqJdu3YAgNzcXHh7eyscERGpndEIREY6FuApKXJ19MBAwN2v77HwJiIiIiIHGo0GkZGR9ttERFXFwwOIiADq1HEswG1D0N21AGfhTUREREQOvLy8cPbsWaXDICI3VrYAv3RJLsJ2/rzsgLvjIBsW3kRERERERKQIDw8gPLy0A372LJCWJhdncycsvImIiIiIiEhRBkNpAX7pEpCeLotyd8HCm4iIiIgcFBYW4vHHHwcAfP755zC5W+uJiFyWwQDUry8Pd8LCm4iIiIgcWCwWrFu3zn6biIjuDAtvIiIiInLg4eGBJUuW2G+T+9qzZw8AYO/evejYsaPC0RC5rxqyXTkRERERVZTBYMCYMWMwZswYGAwGpcMhJ5o5802Hf4lcRUlJidIhVCkW3kRERERENdD27duxfftPAICff96GHTt2KBwRkbRz507UqlUbu3btUjqUKsPCm4iIiIgcWK1WJCYmIjExEVarVelwyEmmT58Bna4lAECna4Hp02coHBGR9PLL05GVlYmXX56udChVhoU3ERERETkoKChAy5Yt0bJlSxQUFCgdDjnB9u3bsW3bD7BYXgQAWCwvYuvW79n1JsXZfjeBYW71O8nCm4iIiIiuExISgpCQEKXDICeR3e5WAPr8eU9f6HTR7HqT4kp/N5e51e8kC28iIiIicuDt7Y309HSkp6fD29tb6XCoipV2u19DaTmghcXymlt1GEl9HH83dW71O8nCm4iIiIioBintKA645pGBbtVhJPW5/nfTfX4nWXgTEREREdUQ5Xe7bdj1JuW4+0gMFt5ERERE5KCwsBBPPvkknnzySRQWFiodDlWh6dNnQKMJBmAE8A2ALX8+suXPj03QaILdosNI6uLuIzH0SgdARERERK7FYrFg5cqVAIAlS5YoHA1VFYvFgj17dkGIfAB9/7zXE8AqAIMAyBXshQB2794Ji8UCnU6nTLBUo5SuZP4lbjwSYxB27NiBTp06KRDhnWPhTUREREQOPDw8sHDhQvttcg86nQ4XL15ATk6O/T6LxYKDBw/i2LFjDkW2r68vi26qNraRGELYRmJcq3Qkxo8/binncdfHwpuIiIiIHBgMBkyaNEnpMMgJ/Pz84OfnZ/+4pKQEBw8eRFhYGAwGg4KRUU1V/kiM66l9JAYLbyIiIiIiIlJEeSMxbkTNIzFYeBMRERGRA6vViqSkJABAREQEtFqux0tEznPtSAx3xMKbiIiIiBwUFBSgYcOGAIDc3Fx4e3srHBERkbqx8CYiIiKi63h5eSkdAhGR22DhTUREREQOvL29kZeXp3QYRERugxN2iIiIiIiIiJyIhTcRERERERGRE7HwJiIiIiIHRUVFGDNmDMaMGYOioiKlwyEiUj0W3kRERETkwGw2Y+nSpVi6dCnMZrPS4RARqR4XVyMiIiIiBwaDAW+88Yb9NhER3RkW3kRERETkwMPDAy+//LLSYRARuQ0ONSciIiIiIiJyIna8iYiIiMiBEAKXL18GAISEhECj0SgcERGRurHwJiIiIiIH+fn5qF27NgAgNzcX3t7eCkdERKRubl94CyEAANnZ2QpHcnMlJSXIz89HdnY2FzFRCeZM3Zg/9WMO3QPz6Jry8vLst7Ozs2GxWG54LnOobsyf+jBnrsNWY9pqzptx+8I7JycHABAeHq5wJERERETqU7duXaVDICJyaTk5OfD397/pORpRkfJcxaxWK1JTU+Hr6+vS85Oys7MRHh6O5ORk+Pn5KR0OVQBzpm7Mn/oxh+6BeVQ/5lDdmD/1Yc5chxACOTk5qFu3LrTam69b7vYdb61Wi/r16ysdRoX5+fnxBaQyzJm6MX/qxxy6B+ZR/ZhDdWP+1Ic5cw236nTbcDsxIiIiIiIiIidi4U1ERERERETkRCy8XYTRaMRrr70Go9GodChUQcyZujF/6sccugfmUf2YQ3Vj/tSHOVMnt19cjYiIiIiIiEhJ7HgTERERERERORELbyIiIiIiIiInYuFNRERERERE5EQsvImIiIiIiIiciIU3ERHVOFarVekQiIiIqAZh4e0G+AaSqHpdunQJqampSodBt+nYsWNYtGiR0mEQEQBurqN+fB9KVDF6pQOg25eVlQV/f39otVpYrVZotbyO4urOnDmDr776Cunp6bj33nvRr18/pUOiSjp48CAGDBiAZcuWoW7dukqHQ5V0+PBhtG3bFsXFxejQoQPuuecepUOi23T27Fls2bIFBQUFaNy4MR566CGlQ6JKyMjIQFBQEDQaDYQQ0Gg0SodElcT3oerC96DK4ytEpY4ePYrIyEjMmjULAOx/9Mh1/fbbb+jSpQs2bNiAn376Cf3798f69euVDosqISEhAZ07d8bAgQNx//33Kx0OVVJCQgLatWuHIUOGoGvXrtiwYQMAdmvU6PDhw7jnnnuwatUqrF27Fn379sXw4cOxd+9epUOjCjh69ChCQ0MxadIkALAX36QefB+qLnwP6hpYeKtQSkoKnnrqKYSGhmL+/PmYM2cOAP7Rc2UnTpxAnz59MGzYMHzzzTfYsGEDHnroIaSkpCgdGlVQYmIiOnfujAkTJuDtt9+GxWLBoUOHsHPnTiQmJiodHt3CwYMH0blzZ0yZMgUrVqxA27Zt8cEHHyArKwtarZZv+lXkypUrGDZsGMaMGYMff/wRW7duxYYNG/DZZ5/hjTfewNatW5UOkW4iNTUVo0aNQqtWrbB06VJMnjwZAItvNeH7UHXhe1DXwaHmKmO1WvHll1+iYcOG+Pvf/469e/farza++OKLHO7jgoqLizFjxgx0794dM2fOhE6ng4eHBzw9PbF79278+uuviI2NxZNPPonAwEClw6VyFBUVYdiwYfDx8cGzzz4LABg0aBDOnTuHc+fOoaioCK+99hqmTp2qcKRUnrS0NHTs2BHjx4/HG2+8AQCYMGEC1q9fj0WLFmH69Okc5qoimZmZ0Ov1GDp0KIQQKCkpQevWrdGsWTPs27cP7777Llq3bs2/py5ICIGtW7ciMjISkyZNwrlz5zBq1ChoNBosWLCAw85VgO9D1YXvQV0LC2+V0Wq16N27N2rXro1u3bqhdevWEEJg9uzZAPhHzxV5eHhg2rRpSE1NhU6nAwDMmjULa9euxRNPPAGTyYSJEyfi+PHjeOeddxSOlspjNBqxYMECjB07FpMnT8aJEycQEhKCf/3rXzCZTNi1axeeffZZ+Pr6YuzYsUqHS9cwGAz49ttv0aVLF/t9oaGhiI2NxXfffYfp06cDAN/wq0ROTg4OHDiAixcvonnz5vDw8EB+fj7Cw8Mxbdo0PPXUU3jwwQcxZswYpUOla2g0GnTp0gW+vr7o0KEDOnToACEERo8eDSEEFi5cyOLbxfF9qLrwPaiLEaRKVqvVfjs9PV3MmTNH+Pn5idmzZwshhDCbzWL9+vUiPT1dqRDpBn777TfRo0cPsWnTJnsev/jiC6HX68WxY8cUjo6uVfa1tnXrVlGnTh3RtWtXkZqa6nDelClTRHR0tLhy5YrDc8j1WCwWIYQQR44cEUajUXz00UcKR0SVUVJSIoYNGyaioqLEu+++K1atWiUCAwNFfHy8EEKISZMmiccff1yUlJTwtagCZrNZrFy5UhiNRjF58mQhhMzxp59+Kg4fPqxwdHQjfB+qTnwPqix2vFUgNTUV58+fx5UrV9CjRw9otVpotVqYzWbo9XqEhIRg9OjRAORVLCEErly5gkWLFiEpKUnh6GumG+UMAKKjo/Hxxx8jLCzMfr5Wq0Xz5s0REhKiVMh0jbI57N69OwDgvvvuw4YNG3D06FHUqlXL4XyTyQQvLy8EBgayU+MCbvQatHVhhBBo2LAh+vbti2+++QZDhw6F0Whk7lxQ2Vz27NkTer0eL7zwAt577z289tprqFOnDuLj4+3TCLKysnD16lXo9XyL4wpKSkpgMBhu+LhOp8Njjz0GABg1ahQAwGKxYPHixTh16lS1xEg3x/eh6sL3oC5M4cKfbiEhIUGEh4eL5s2bC71eL2JjY8XixYtFTk6OEEJeUbRJT08Xs2fPFhqNRgQGBop9+/YpFXaNdqucCSGu68JMnTpV9O7dW2RnZ1d3uFSO8nL43nvviaysLCGEEMXFxdc9Z+zYsWL06NGiqKiIXTaF3eo1aOt4CyHEZ599JoxGo9i7d69S4dJNXJvL1q1biyVLloj8/HwhhBApKSkOo0+sVqsYPny4eOGFF4TVauVrUWFHjhwRDz/8sEhMTLzluWazWXzyySd8D+Ni+D5UXfge1LWx8HZh6enpolmzZuKFF14QZ86cEWlpaeKJJ54Q99xzj5g0aZL9BVL2TeSwYcOEn59fhf6To6pX0ZzZpKamildeeUUEBARwSJ2LuJ0cvvrqqyIwMJCvOxdQ0fyVfbMYGxsrhg0bJiwWCws1F3KjXLZt21ZMmjRJZGZmOpx/+vRpMW3aNBEQECCOHj2qUNRkc+bMGdGoUSOh0WhE69atxfHjx296vsViEU8//bTw8/Nj/lwE34eqC9+Duj4W3i7s8OHDokGDBiIhIcF+X1FRkZg+fbpo166dePnll0VBQYEQQl69+uSTT0RoaKj49ddflQq5xqtMzvbv3y+eeuop0bBhQ3Hw4EGFIqZrVSaHe/fuFY899pioX78+c+giKpM/m0WLFomTJ09Wd6h0C5XJZXp6uhg7dqxo0qSJOHDggFIh058KCwvF66+/LgYOHCj27dsn2rVrJ5o1a3bT4nvTpk2iYcOG7JK6EL4PVRe+B3V9XG7QhXl4eECj0djnx5jNZnh4eODVV19F165dsXHjRuzbtw+AXCm0Y8eO2LNnD+Li4pQMu0arTM7q1KmDwYMH44cffkDr1q0VjJrKqkwOw8LCMHjwYGzbto05dBGVyZ/ZbAYATJw4EVFRUYrFTOWrTC5DQkIwdepU/PDDD4iNjVUybILcSSA6OhpDhw5FmzZtsHnzZvj6+mLAgAE4ceJEuc+JiYnBzp070aZNm2qOlm6E70PVhe9BXZ9GCCGUDoLKV1RUhE6dOqFOnTr46quvoNPp7AtZCCEQExOD2NhYrFixgltvuIiK5Kx169b4+OOPlQ6VboA5VLfK/N0k18ZcqpvFYrFvXwQAV65cQe/evZGTk4N169ahcePGMJvN2Lt3L+Li4mAymRSMlsrD96Hqwvcvro8dbxdltVphNBqxbNky/Pzzzxg3bhwA2F88Go0GDz/8MNLS0gCAf+xcQEVzlp6ernCkdCPMobpV9u8muS7mUv1sRbetvxMcHIyNGzfC19cX/fv3R2JiIiZMmIDJkycjLy9PyVCpHHwfqi58/6IOLLxdlFarhcViQcuWLbFixQqsWrUKw4cPx6VLl+znnDlzBoGBgbBYLApGSjbMmfoxh+rG/LkP5lL9bAW3rSATQiAkJASbNm1CQEAAWrVqhRUrVuC9995DcHCwkqFSOfgaVBfmSx041NxF2YaG5ObmoqioCIcOHcLQoUMRGRmJoKAgBAcHY926ddi1axeio6OVDpfAnLkD5lDdmD/3wVyqm22YeXZ2NqxWKwICAhweHz16NNavX4+ff/4ZzZs3VyZIcnDtUHG+Bl0b86VO7Hi7INuL5+zZs7j77ruxb98+dO/eHYmJiejduzfq1auH2rVrY+/evXzxuAjmTP2YQ3Vj/twHc6luZrMZOp0OZ8+eRbNmzbBr1y77Y0IIvPPOO1i+fDm2bNnCotsF2Lqftj6cEIKvQRfGfKkbO94KOnPmDDZv3owTJ07goYceQmxsLEJCQgAAycnJiIuLQ//+/fHhhx/CarVCp9PZr3BZrVZotbxuUt2YM/VjDtWN+XMfzKW6VSR/AwYMwJIlSxyGm//000+oX78+dxJwASdOnMDixYuRlJSEmJgYDBs2DA0bNgTA16ArYr7Uj4W3Qg4fPowHH3wQMTExOHXqFLRaLUaPHo0pU6bAarViyZIlOH36NObPn+8wlMT2AuLqkdWPOVM/5lDdmD/3wVyq2+3mj1zH4cOH0a1bN/Tt2xdZWVm4ePEi+vXrh5deeglmsxkffPABTp8+jQULFvA16AKYLzdRdVuCU0WdPXtWNG7cWEybNk0UFxcLIYR48cUXRVRUlH1j+8zMTCVDpGswZ+rHHKob8+c+mEt1Y/7U7/Tp0yIyMlK8/PLL9vuefvppMXHiRIfzzGZzdYdG5WC+3AfHHFQzi8WCdevWITY2FhMmTLAP+5g0aRKKi4tx4sQJAIC/v7+SYVIZzJn6MYfqxvy5D+ZS3Zg/9bNYLNiyZQu6d++OKVOm2OcKe3p64siRI+jatSuGDx+OnTt32ocqk3KYL/fCwrua6XQ6+Pv7o2PHjqhTp459n0uNRoPs7GxkZGRc9xy+iJTFnKkfc6huzJ/7YC7VjflTP51OhwceeADPPfccAgMDodFo8H//939YunQpevTogfvuuw/FxcUYNmwYzpw5w+HJCmO+3Ite6QBqohEjRthviz/nXPj5+aFOnTrw8vKyP7Z+/XrExsYiPDxciTCpDOZM/ZhDdWP+3AdzqW7Mn/o1bNjQfkGkqKgIe/bswRdffIE+ffoAAHbs2IFHH30Up06dsi/eRcphvtwHC+9qkJqaigMHDqC4uBgRERFo06YNgNJ9LgG58b1Wq7VfqZo2bRqWLVuGPXv2KBZ3TcacqR9zqG7Mn/tgLtWN+VO/sjmMjIzEX/7yF2g0GlgsFhiNRnz99dfQarX2la+DgoIQGhqKoKAgpUOvkZgvN1bdk8prmt9++000atRItGvXToSEhIg2bdqI1atXX3fe1atXRa1atcQvv/wiZs6cKUwmk9i3b58CERNzpn7Moboxf+6DuVQ35k/9KpJDq9Xq8PGLL74o2rZtK9LT06szVBLMl7tj4e1Ep06dEvXr1xfPP/+8yMzMFPv37xcjRowQo0ePFmaz2eGFk5OTI2JjY8V9990nTCaT2L9/v4KR11zMmfoxh+rG/LkP5lLdmD/1q0wOhRDi3LlzYurUqSIwMFAkJCQoFHXNxXy5PxbeTlJUVCSee+45MXjwYFFUVGS//6OPPhLBwcHi8uXLDudnZmaKyMhIERQUJA4dOlTd4ZJgztwBc6huzJ/7YC7VjflTv8rmcN++fSI+Pl7ExMQwhwpgvmoGzvF2EqvVivr166NZs2bw8PCwL0DSoUMH+Pj4oKSkxOF8f39/jBkzBo8++iiaNm2qUNQ1G3OmfsyhujF/7oO5VDfmT/0qm8M2bdqgoKAAr7zyCsLCwhSKuuZivmoI5Wp+9/fHH3/Yb9uGh1y4cEFERUWJpKQk+2OcB+U6mDP1Yw7VjflzH8ylujF/6lfRHHJqgGtgvtwf9/GuQhcuXMDevXvx7bffwmq12pf0t1gs9pU+s7KycPXqVftzpk+fjgceeABXrlzhXpcKYM7UjzlUN+bPfTCX6sb8qd/t5rBnz57MoQKYrxpIuZrfvSQkJIjIyEhx9913C39/f9G0aVOxcuVKceXKFSFE6ZWr48ePi1q1aomMjAwxc+ZM4enpyStXCmHO1I85VDfmz30wl+rG/Kkfc6guzFfNxMK7CqSlpYmmTZuKadOmidOnT4vz58+LIUOGiGbNmonXXntNpKWl2c+9dOmSiI2NFUOGDBEeHh588SiEOVM/5lDdmD/3wVyqG/OnfsyhujBfNRcL7yqQmJgoGjRocN2L4YUXXhDR0dFi3rx5Ii8vTwghxNGjR4VGoxGenp7i4MGDCkRLQjBn7oA5VDfmz30wl+rG/Kkfc6guzFfNxTneVaCkpARmsxn5+fkAgIKCAgDAnDlz0K1bNyxevBinTp0CAAQGBiI+Ph4HDhxA69atlQq5xmPO1I85VDfmz30wl+rG/Kkfc6guzFfNpRGCM/OrQrt27eDj44Mff/wRAFBUVASj0QgAaNu2LaKiorBq1SoAQGFhIUwmk2KxksScqR9zqG7Mn/tgLtWN+VM/5lBdmK+aiR3v25CXl4ecnBxkZ2fb7/vggw+QmJiIoUOHAgCMRiPMZjMAoEuXLsjLy7OfyxdP9WPO1I85VDfmz30wl+rG/Kkfc6guzBfZsPCupKNHj+KRRx5B165d0axZM3z22WcAgGbNmmHRokXYsmULHnvsMZSUlECrlT/etLQ0eHt7w2w2c+l/BTBn6sccqhvz5z6YS3Vj/tSPOVQX5ovK0isdgJocPXoUXbp0wfDhw9GmTRv8+uuvGDVqFJo3b47Y2Fg8/PDD8Pb2Rnx8PFq1aoWmTZvCw8MDGzduxO7du6HX88dd3Zgz9WMO1Y35cx/Mpboxf+rHHKoL80XX4hzvCsrIyMATTzyBpk2bYtGiRfb7u3XrhujoaPzrX/+y35eTk4M33ngDGRkZMJlMGDduHJo3b65E2DUac6Z+zKG6MX/ug7lUN+ZP/ZhDdWG+qDy8lFJBJSUlyMzMxKBBgwAAVqsVWq0WDRs2REZGBgBAyO3Z4Ovri7lz5zqcR9WPOVM/5lDdmD/3wVyqG/OnfsyhujBfVB5mtoJCQ0Px6aefonPnzgAAi8UCAKhXr579BaLRaKDVah0WT9BoNNUfLAFgztwBc6huzJ/7YC7VjflTP+ZQXZgvKg8L70po3LgxAHk1ymAwAJBXq9LS0uznzJ49G0uXLrWvTMgXkLKYM/VjDtWN+XMfzKW6MX/qxxyqC/NF1+JQ89ug1WohhLC/OGxXrqZPn4433ngDBw8e5IIILoY5Uz/mUN2YP/fBXKob86d+zKG6MF9kw473bbKtSafX6xEeHo5//vOfmDdvHvbv34+YmBiFo6PyMGfqxxyqG/PnPphLdWP+1I85VBfmiwB2vG+b7WqVwWDAhx9+CD8/P+zYsQNxcXEKR0Y3wpypH3Oobsyf+2Au1Y35Uz/mUF2YLwLY8b5jvXr1AgDs3LkTbdq0UTgaqgjmTP2YQ3Vj/twHc6luzJ/6MYfqwnzVbNzHuwrk5eXB29tb6TCoEpgz9WMO1Y35cx/Mpboxf+rHHKoL81VzsfAmIiIiIiIiciIONSciIiIiIiJyIhbeRERERERERE7EwpuIiIiIiIjIiVh4ExERERERETkRC28iIiIiIiIiJ2LhTURERERERORELLyJiIgIGo0GX331ldJhEBERuSUW3kRERAoaOXIkNBoNxo4de91j48ePh0ajwciRI6vs673++uto3br1bT//8uXLqFOnDmbNmnXdY4MHD0b79u1hsVjuIEIiIiL3w8KbiIhIYeHh4fj8889RUFBgv6+wsBArV65ERESEgpFdLyQkBEuWLMGMGTNw+PBh+/2rV6/Ghg0bsGLFCuh0uir9mhaLBVartUo/JxERUXVi4U1ERKSwuLg4hIeHY82aNfb71qxZg4iICMTGxtrvKyoqwsSJE1G7dm2YTCZ06tQJ+/btsz++bds2aDQa/PDDD2jTpg28vLzQoUMHHD9+HACwfPlyzJgxAwkJCdBoNNBoNFi+fLn9+ZcvX8bAgQPh5eWFxo0bY/369eXG+/DDD2Po0KEYMWIESkpKkJ6ejvHjx2POnDlo0qQJ1q1bh7i4OJhMJjRq1AgzZsyA2Wy2P3/BggWIjo6Gt7c3wsPDER8fj9zcXPvjy5cvR0BAANavX4/mzZvDaDQiKSnpjn/ORERESmHhTURE5AJGjx6NZcuW2T/+z3/+g1GjRjmc8/zzz+PLL7/EihUrcODAAURFRaFXr17IyMhwOO/ll1/G/PnzsX//fuj1eowePRoAMGTIEEyZMgUtWrTAhQsXcOHCBQwZMsT+vBkzZmDw4MH47bff0Lt3bzz55JPXfW6bRYsW4cqVK5g5cybi4+PRsmVLTJgwAdu3b8fw4cPx7LPP4ujRo/jggw+wfPlyvPnmm/bnarVa/Otf/0JiYiJWrFiBH3/8Ec8//7zD58/Pz8fcuXOxdOlSJCYmonbt2rf3gyUiInIFgoiIiBQzYsQI0b9/f5GWliaMRqM4e/asOHv2rDCZTCI9PV30799fjBgxQuTm5gqDwSA+++wz+3OLi4tF3bp1xbx584QQQmzdulUAEN9//739nI0bNwoAoqCgQAghxGuvvSZiYmKuiwOAeOWVV+wf5+bmCgDim2++uWHsP/zwg9DpdMLPz0+cPXtWCCFE9+7dxaxZsxzO++STT0RYWNgNP8/q1atFcHCw/eNly5YJAOLQoUM3fA4REZGa6BWt+omIiAgAUKtWLfTp0wfLly+HEAJ9+vRBSEiI/fHTp0+jpKQEHTt2tN9nMBjQrl07/P777w6fq1WrVvbbYWFhAIC0tLRbzhcv+zxvb2/4+fkhLS0NANCiRQucO3cOANC5c2d88803uP/++9G+fXu0bt0akZGRAICEhAT88ssvDh1ui8WCwsJC5Ofnw8vLC99//z1mz56NY8eOITs7G2az2eFxAPDw8HCIh4iISM1YeBMREbmI0aNH4+9//zsA4L333rvtz2MwGOy3NRoNAFRocbKyz7M91/a8TZs2oaSkBADg6elpP0ev10OvL307kZubixkzZuCRRx657vObTCacPXsWffv2xbhx4/Dmm28iKCgIO3bswNNPP43i4mJ74e3p6WmPnYiISO1YeBMREbmIBx98EMXFxdBoNOjVq5fDY3fddRc8PDzwyy+/2LvLJSUl2LdvHyZNmlThr+Hh4XFb233ZvuatxMXF4fjx44iKiir38V9//RVWqxXz58+HViuXmvnf//5X6XiIiIjUhIU3ERGRi9DpdPZh49duyeXt7Y1x48Zh6tSpCAoKQkREBObNm4f8/Hw8/fTTFf4aDRo0wJkzZ3Do0CHUr18fvr6+MBqNVfY9TJ8+HX379kVERAQGDRoErVaLhIQEHDlyBG+88QaioqJQUlKCd955B/369cMvv/yC999/v8q+PhERkSviquZEREQuxM/PD35+fuU+NmfOHDz66KMYNmwY4uLicOrUKWzevBmBgYEV/vyPPvooHnzwQXTr1g21atXCqlWrqip0AECvXr2wYcMGfPfdd2jbti3at2+PhQsX2jvmMTExWLBgAebOnYuWLVvis88+w+zZs6s0BiIiIlejEUIIpYMgIiIiIiIiclfseBMRERERERE5EQtvIiIiIiIiIidi4U1ERERERETkRCy8iYiIiIiIiJyIhTcRERERERGRE7HwJiIiIiIiInIiFt5ERERERERETsTCm4iIiIiIiMiJWHgTERERERERORELbyIiIiIiIiInYuFNRERERERE5EQsvImIiIiIiIic6P8BfVaeYXhZUFkAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Function to plot the trend and its 95% CI\n",
    "def plot_trend_with_ci(dff, label, color):\n",
    "    plt.plot(dff['month_year'], dff['mean_trend'], color=color, label=f'{label}')\n",
    "    plt.fill_between(dff['month_year'], dff['lower_ci'], dff['upper_ci'], color=color, alpha=0.2)\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "# Panel Before November 2022\n",
    "plot_trend_with_ci(bef_panel, label='Panel Trendlines with 95% CI', color='orange')\n",
    "# Panel After November 2022\n",
    "plot_trend_with_ci(aft_panel, label='', color='orange')\n",
    "# Decahose Before November 2022\n",
    "plot_trend_with_ci(bef_deca, label='Decahose Trendlines with 95% CI', color='blue')\n",
    "# Decahose After November 2022\n",
    "plot_trend_with_ci(aft_deca, label='', color='blue')\n",
    "\n",
    "# Adjust scatter plot markers to differentiate\n",
    "# Panel\n",
    "# Adjust scatter plot markers to differentiate\n",
    "# Panel\n",
    "plt.scatter(info_qual_panel.month_year, info_qual_panel.weighted_average, \n",
    "            color='orange', label='Actual Panel', marker='o', s=50, edgecolor='black')\n",
    "# Decahose\n",
    "plt.scatter(info_qual_decahose.month_year, info_qual_decahose.weighted_average, \n",
    "            color='blue', label='Actual Decahose', marker='^', s=50, edgecolor='black')\n",
    "\n",
    "# Add vertical line and annotation for the event\n",
    "plt.axvline(x=complete_nov, color='black', ls=\":\")\n",
    "plt.text(x=complete_nov, y=83, s='Elon Musk buys Twitter', color='black', ha='right', va='bottom', fontsize=11, rotation=90)\n",
    "\n",
    "# Customize plot\n",
    "plt.xlabel('Month-Year')\n",
    "plt.ylabel('Information Quality')\n",
    "plt.title('Information Quality by Time with before and after trendlines')\n",
    "plt.legend()\n",
    "plt.xticks(rotation=45)\n",
    "plt.tight_layout()\n",
    "plt.grid()\n",
    "#\n",
    "#plt.savefig('/home/ozturan/covid-conspiracy-narratives/src/musk/submission/figures/fig1_bootstrapped_ci.png',dpi=1200,bbox_inches='tight')\n",
    "plt.show"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68ec278c-ee5a-4ad4-8a1c-39d797e151eb",
   "metadata": {},
   "source": [
    "# Interrupted Time Series Analysis (ITS) Table 1 and Table 2 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f0c5fc41-55fd-4d0b-a099-2915ffebb5a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings \n",
    "warnings.filterwarnings('ignore')\n",
    "info_qual_panel['info_qual'] = info_qual_panel['weighted_average']*1\n",
    "\n",
    "\n",
    "info_qual_panel['info_qual'] = info_qual_panel['weighted_average']*1\n",
    "\n",
    "# Create a time variable\n",
    "info_qual_panel['time'] = np.arange(len(info_qual_panel))\n",
    "# Create an intervention variable\n",
    "info_qual_panel['intervention'] = (info_qual_panel.month_year >= '2022-10-27').astype(int)\n",
    "# Create a time after intervention variable\n",
    "info_qual_panel['time_after_intervention'] = np.where(info_qual_panel.month_year >= '2022-10-27', info_qual_panel['time'] - info_qual_panel['time'][info_qual_panel['intervention'] == 1].min(), 0)\n",
    "# Perform ITS analysis using OLS regression                       "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "013a496c-1687-475d-bb2e-6a6f64804909",
   "metadata": {},
   "outputs": [],
   "source": [
    "info_qual_decahose['info_qual'] = info_qual_decahose['weighted_average']*1\n",
    "info_qual_decahose['time'] = np.arange(len(info_qual_decahose))\n",
    "# Create an intervention variable\n",
    "info_qual_decahose['intervention'] = (info_qual_decahose.month_year >= '2022-10-27').astype(int)\n",
    "\n",
    "# Create a time after intervention variable\n",
    "info_qual_decahose['time_after_intervention'] = np.where(info_qual_decahose.month_year >= '2022-10-27', info_qual_decahose['time'] - info_qual_decahose['time'][info_qual_decahose['intervention'] == 1].min(), 0)\n",
    "# Perform ITS analysis using OLS regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b987e938-db6e-4610-b0f8-f4dccb43c95f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:              info_qual   R-squared:                       0.757\n",
      "Model:                            OLS   Adj. R-squared:                  0.697\n",
      "Method:                 Least Squares   F-statistic:                     12.87\n",
      "Date:                Tue, 12 Nov 2024   Prob (F-statistic):           0.000465\n",
      "Time:                        13:30:40   Log-Likelihood:                -11.875\n",
      "No. Observations:                  16   AIC:                             31.75\n",
      "Df Residuals:                      12   BIC:                             34.84\n",
      "Df Model:                           3                                         \n",
      "Covariance Type:                  HAC                                         \n",
      "===========================================================================================\n",
      "                              coef    std err          z      P>|z|      [0.025      0.975]\n",
      "-------------------------------------------------------------------------------------------\n",
      "Intercept                  83.7815      0.242    346.616      0.000      83.308      84.255\n",
      "time                        0.3430      0.063      5.451      0.000       0.220       0.466\n",
      "intervention               -1.4523      0.547     -2.653      0.008      -2.525      -0.379\n",
      "time_after_intervention    -0.7086      0.123     -5.758      0.000      -0.950      -0.467\n",
      "==============================================================================\n",
      "Omnibus:                        2.779   Durbin-Watson:                   1.217\n",
      "Prob(Omnibus):                  0.249   Jarque-Bera (JB):                1.150\n",
      "Skew:                          -0.145   Prob(JB):                        0.563\n",
      "Kurtosis:                       1.719   Cond. No.                         36.9\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors are heteroscedasticity and autocorrelation robust (HAC) using 1 lags and without small sample correction\n"
     ]
    }
   ],
   "source": [
    "\n",
    "reg = smf.ols('info_qual ~ time + intervention + time_after_intervention', data=info_qual_panel).fit(cov_type='HAC',cov_kwds={'maxlags':1})\n",
    "print(reg.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d737d23b-9052-4900-a4f2-82a05445aa08",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:              info_qual   R-squared:                       0.735\n",
      "Model:                            OLS   Adj. R-squared:                  0.668\n",
      "Method:                 Least Squares   F-statistic:                     17.52\n",
      "Date:                Tue, 12 Nov 2024   Prob (F-statistic):           0.000111\n",
      "Time:                        13:33:45   Log-Likelihood:                -11.971\n",
      "No. Observations:                  16   AIC:                             31.94\n",
      "Df Residuals:                      12   BIC:                             35.03\n",
      "Df Model:                           3                                         \n",
      "Covariance Type:                  HAC                                         \n",
      "===========================================================================================\n",
      "                              coef    std err          z      P>|z|      [0.025      0.975]\n",
      "-------------------------------------------------------------------------------------------\n",
      "Intercept                  84.8663      0.237    358.499      0.000      84.402      85.330\n",
      "time                        0.0802      0.032      2.497      0.013       0.017       0.143\n",
      "intervention               -1.3904      0.434     -3.201      0.001      -2.242      -0.539\n",
      "time_after_intervention    -0.3471      0.123     -2.823      0.005      -0.588      -0.106\n",
      "==============================================================================\n",
      "Omnibus:                        1.040   Durbin-Watson:                   2.005\n",
      "Prob(Omnibus):                  0.595   Jarque-Bera (JB):                0.074\n",
      "Skew:                          -0.016   Prob(JB):                        0.963\n",
      "Kurtosis:                       3.333   Cond. No.                         36.9\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors are heteroscedasticity and autocorrelation robust (HAC) using 1 lags and without small sample correction\n"
     ]
    }
   ],
   "source": [
    "reg = smf.ols('info_qual ~ time + intervention + time_after_intervention', data=info_qual_decahose).fit(cov_type='HAC',cov_kwds={'maxlags':1})\n",
    "print(reg.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f12bd08-7da9-49f0-ba3a-955d4e763af1",
   "metadata": {},
   "source": [
    "# Market Share Change Analysis Figure 2 and Figure 3 "
   ]
  },
  {
   "cell_type": "raw",
   "id": "b024b8a7-2d71-4d1b-b7f2-6d40c05c1401",
   "metadata": {},
   "source": [
    "# Define custom intervals\n",
    "intervals = [(0, 39),(40, 59),(60, 74),(75, 100)]\n",
    "\n",
    "# Initialize lists for storing results\n",
    "x_deca = []\n",
    "y_deca = []\n",
    "y_deca_vol = []\n",
    "\n",
    "for interval in intervals:\n",
    "    lower, upper = interval\n",
    "    \n",
    "    # Filter dataframe based on the custom interval\n",
    "    filtered_df = merged_df[(merged_df['Score'] > lower) & (merged_df['Score'] <= upper)]\n",
    "    \n",
    "    # Calculate daily sum and ratios\n",
    "    daily_sum = filtered_df.groupby('date')['count'].sum()\n",
    "    daily_sum_all = merged_df.groupby('date')['count'].sum()\n",
    "    daily_ratio = daily_sum / daily_sum_all\n",
    "    \n",
    "    # Calculate relative changes in the interval-defined groups\n",
    "    change = (daily_sum[299:485].mean() - daily_sum[:299].mean()) / daily_sum[:299].mean()#299is the date for the intervention and 485 is the last data point so 299:485 is the after period whereas 0:299 is the before period \n",
    "    change_r = (daily_ratio[299:485].mean() - daily_ratio[:299].mean()) / daily_ratio[:299].mean()\n",
    "    \n",
    "    # Append results\n",
    "    x_deca.append(f\"{lower}-{upper}\")\n",
    "    y_deca.append(change_r * 100)\n",
    "    y_deca_vol.append(change * 100)\n",
    "\n",
    "# Print results\n",
    "print(y_deca)\n",
    "print(y_deca_vol)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "987454e1-dd22-44cb-b5ae-d2135e52e93d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#the code above was used to calculate the numbers for the below. Due to newsguard datasharing policies,\n",
    "#we cannot share the raw data how many times each domain is shared with their newsguard scores but the above code \n",
    "#when applied to decahose data gives number below\n",
    "\n",
    "y_deca = [np.float64(14.490580136553247), np.float64(27.907925560401715), np.float64(12.358032547184624), np.float64(-4.064932402646688)]\n",
    "y_deca_vol = [np.float64(-2.966713707556838), np.float64(9.591486860574573), np.float64(-3.3498918641170112), np.float64(-18.200476649838887)]\n",
    "\n",
    "\n",
    "# when the same code is applied to Twitter panel data we got these results:\n",
    "\n",
    "y =[np.float64(-0.5133828762590024), np.float64(30.34334335552621), np.float64(4.194735328550365), np.float64(-1.2410372714592508)]\n",
    "\n",
    "y_vol = [np.float64(-28.17740858352895), np.float64(-4.896890581809054), np.float64(-24.70280940861409), np.float64(-26.906682891237455)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "78f20a00-996a-48d8-80bd-40401d2502c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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dHz58aDCvWq0WW1tbqV69unTo0EHatGkjJUuWFABiZ2cn+/fvN5gnLCxMAEjfvn3FyspK/Pz8pEuXLtK6dWuZNm2aiOTu+fLjjz9m2K79+OOPSr65c+cq147AwEDp3r271K1bVzl+xo0bl6O6ZIfu/HzxPNJd9//++2+99L59+yrlGzJkiN60nTt3CgBp1KiRXrqxtjEsLEy5LlSuXFnv+Pvxxx+zdW34559/xMfHRwCIp6enNG/eXFq3bq3MW6VKFYNjSVfvHj16iLOzs3h4eEjHjh2lQ4cOWT7+ddvBWJuflpYmVlZWAkC++uorERH54osvBICUKFFCmjRpovTBdH2iDh06iFar1VtO+rYgLCxMLCwspHHjxtKlSxflWmVlZSV//fWXQRmy2yaIiNLeZbddfZW2MCftwFdffaUsu2bNmtK9e3elbRw6dKjR9vNldNtlwYIFmebTarXi7OwsAGTSpEl603LajuzYsUOcnJwEgLi5uUnbtm2lc+fOUqNGDbGwsJCwsDC9/Kbe3tltq9LS0qRJkyYCQBwdHaVFixbSvXt3CQkJUbbz8ePH9ebJyfGaGd25A0CuXLmSad6TJ08qeQ8ePKg3Lbv9nmHDhkm9evWUfkP6div98ZKT9mDHjh1iYWGhtJudOnWS9u3bS82aNcXKykratm1rULfs/BbLarubk3LQ649BqQKqZ8+eAkAaN26co/l1HSIAEh4ertehv379uhQrVkwAyLJly/Tmi4+Pl99++03vx4iISHJysowaNUoASMuWLQ3Wp+sUApAffvhBb9rOnTuVQMONGzf0pg0ZMkQASPny5eX27dtK+tOnT6VTp07KMl/8ob1lyxZRqVTi6uoqe/bs0Zt26tQp8fb2FgDyxx9/KOnjx48XANKvXz+Dhjg5OVl27NhhUK/M6Mr2It0FzsLCQjZs2KA3TXfR1mg08uTJkyytR9cRByDXr1/PVhlFnv3Q1P04nzBhgl7dDx8+LEWKFBEAMnfuXL35cnoMZaXTOXfuXAEgpUqVkpMnT+pN27Nnjzg4OIilpaWcP39eb5quPE5OTgadZF15y5QpY7C+lwV0XmbdunVKh+/Fc0NEJCQkRADI6NGjlbTZs2cLAHF1ddXrHGm1WqWsTk5Ocv/+/SyV9VWDUgDkvffek5SUFGXa+vXrBYA4ODiIr6+vwfHx9ddfK/vpRT169BAA0qpVK7l3757etBkzZggAKV26dLaC6mvXrpWYmBij6ebm5uLi4mJw3uT0OP3999+VQMOff/6pN+3LL79UlvkqQanIyEiDdjwtLU2KFy8udnZ2Eh8fn2lQatOmTXrtos6BAwfE0dFRLCws5ObNm3rTdG0MAGnSpInExcUZzG8sKPXPP/8obdenn36ql1+r1Sqd4D59+kh8fLwyLSUlRQkwvxgsyOkPUB3dcQQ8C2z17dtX5s2bJ8eOHcv0uEq/DUJDQ/W2QUxMjFSpUkUAyJdffmkw74oVK+Tx48cG9Z81a5YAkDfeeMPg+qEL5ADPbsykpaUZLDcvzpfM2oRTp06Jubm5qFQqWbx4sd60TZs2KT8Ytm3blu26ZEdGQSldf2LixIl66SVKlBAvLy9xcXGRihUrZmmejLZDRm1iVubVefLkiRIc/fTTT/Xa/4SEBOnevbsAz4L+xtYNPAvwZieoqqOb31jZdO0XANm1a5eIiBw6dEhOnz5tkPfWrVtKgO7XX3/Vm5b+h7Wvr6+cO3dOmZaamioRERECQJo1a6Y3n6nbhFdtC7PTDpw8eVLUarWYmZnJypUr9aYtXbpUVCpVngalRJ73Kd5++2299Jy0I9evX1f6gCNHjjTow9y7d8/gBp0pt3dO2qo9e/YoAaz0x57O4cOHJSoqSvk7p8drZrITlEpLS1Pq8dNPP+lNy0m/R7etXwwmppeT9qBRo0YCGN5IExF5+PChQUAtJ7/FRF7e7ma3HFQwMChVQDVv3lwASLdu3XI0v65D5O3tLQkJCQbT//e//wlgfIRMZry8vMTMzMzgIqBrYDp06GB0Pl190l9wnjx5Ivb29gJAtm7dajDP/fv3xdbW1minslatWgLA6MgJEZFff/1VAEjHjh2VtA8++EAA6I2keRUvC0oNHTrU6HwBAQECwOCHcEZWrFihrCsnHVvd3ZJq1aoZnT5t2jSlI5NeTo+hl3U609LSlBFrR44cMZpnypQpAsDgjrJuO3z77bcG8yQmJiodrxeDd68alEpJSREPDw8BYNBJvXbtmnKXKP0oQt0PGWNl1Wq1UqlSpWz9wHrVoFTx4sXl6dOnBvPpylGzZk2DH9spKSnKHdtr164p6WfPnhWVSiVeXl5GO4QiIi1bthQABoHZnNL9+Nu4caNeek6PU12n/+OPPza6Pl0H+lWCUiIi9erVE5VKpXRat2zZogTQRCTToFRmdD/QZ82apZeu66xaWFjIpUuXjM77YlBq586d4uTkJBYWFkZHKG7evFmAZ3dB0wc1ddLS0qRChQoCQK8T/KpBKRGRiRMnip2dnbJddf8cHBykV69eEhkZaTCPbhvY2dkZ/WGla1Oze9NHN3rwn3/+0UvXBXLKlCljNKiUV+dLZm1Cnz59Mr0mDxgwQABI06ZNs1WX7MooKKW72RIcHKykXbp0Sfmh1blzZwEgd+/eVaZnNLoqL4NSupsLrVq1Mjr90aNH4ubmJubm5no/LHXrdnZ2NjoyJCuMBaUePHggy5YtU0aeVKlSJUuBw61btwoA6dy5s156+h/W69evN5jvzp07AjwbLZV+tGl+tgkvellbmN124J133hEA0rVrV6Pra9u2bZ4Hpbp16yYApEWLFkpaTtuRwYMHCwBp3bp1tsqbkdze3jlpq3R9/IxGr78op8drZrITlBIRpQ85efLkLC1fJON+T1aCUpnJqD3QjdAyFiQzJie/xURe3u5mtxxUMPDre/9xTZo0MfryT91L0TN6vvvkyZPYuXMnrly5goSEBOXZ49TUVGi1Wly8eBGBgYEG87Vu3dro8sqVK4ctW7bore/o0aN4/PgxXF1d0axZM4N5ihYtiqZNmxo8OxwVFYVDhw7BxsYmw/XpnqtO/5x8zZo18f3332PkyJEQETRr1ixPP52d2baIjIzM9Nn63KR7z0ZYWJjR6X369MFHH32ECxcu4Pbt2/Dy8tKbntNjKCPHjx/H7du34e/vj2rVqhnNY2z/pWds21pZWaFkyZI4fvw4bt26BR8fn2yVKzPm5uYICwvD5MmTMX/+fHTq1EmZtmDBAmi1WjRs2BClSpUCANy8eROXLl0CYHy7q1Qq9O7dG0OGDMHu3bsxevToXCtrRho1agRra2uD9NKlS+PUqVNo0aKFwTvSzM3N4efnh5iYGNy+fVv5utWmTZsgImjRogUcHByMri84OBibNm3CgQMH0KpVqyyX8/bt29i4cSMiIyMRFxenvH/hn3/+AQCcO3cOLVu2NJgvO8dpamoq9u3bBwB4++23jZajV69eOHHiRJbLnZGIiAjs378fCxYswPjx45UXn2f1BefR0dHYuHEjzpw5g9jYWKSkpAAALly4AAAZvucoMDAQJUuWfOnyFy1ahL59+8LGxgYbN25E06ZNDfJs3LgRwLPPXpubG3YrzMzM0KBBA5w5cwYHDhxAhQoVslS3rBg9ejQ++OAD/Pbbb9izZw+OHTuGM2fO4NGjR1i8eDFWrlyJVatWGT0mqlevbvTLfC9ruy5evIgtW7bg4sWLePToEdLS0gA8f8fVuXPnUL58eYP52rVrB7VabZCel+dLRnTtfkbvL+rTpw++++477N27F2lpaQblzqguuaVevXqwsbHBwYMH8eTJE9ja2irvqmnatCkSEhKwcuVK7NixA2+99RYePnyIo0ePwsnJCdWrV8+zcr1Id+x37drV6HR7e3tUr14dmzZtwuHDhw36MiEhIdBoNK9UBt272V5UtWpVrFmzBmZmz18fm5SUhG3btuHw4cO4f/8+kpKSICJ49OgRgIzbC3NzczRv3twg3cPDA0WKFEFsbCyio6Ph4eEBIH/ahJy2hdltB3TnTkbXhrCwsDx/p42uz53+mpzTdmTLli0AgH79+mWrDKbe3tlpq6pWrQq1Wo358+ejTJkyyrtJM5Kf1zAdY/tUJ6f9npfJbntQs2ZNnD17Fm+99RZGjx6N2rVrG91eQM5/i2VFdspBBQf3YAFVtGhRAMD9+/dfaTkZfSLZ0dERAAxewJuQkICePXti7dq1mS43Pj7+ldd38+ZNAMj0pbfGpl25cgUigqdPn77006oPHjxQ/r9nz57Yvn07fv75Z3Ts2BFqtRrly5dH/fr10alTJzRu3DjTZWVXdrd9RnTHAvDseMhusEXXAcjo08JOTk5wdnZGTEwMbt68aRCUyq166Fy+fBkAcOnSJaMX5/TS77+8LFNWREREYPLkydi2bRtu3bqFYsWKQUSUFzOmf8G5bpu7uLgoZXqRv7+/Xt68ltE20wVmM5qu6/ym36a6fThv3jy9F6Ubk9E+NGb8+PGYOHGi0vk1JjfanujoaOXvjM6L3PoUd5cuXTBo0CAsWrQIAwcOxG+//YbSpUsb/RjBi3788UcMGTIECQkJGebJaHtk5WXiN2/eVH4I7Nq1C/Xr1zeaT7e/x4wZgzFjxmS6zOzs76xycnJCWFiYEuCNjY3F2rVr8emnn+LOnTsICwvDtWvXDIKS2W0n0tLSMGDAAMyZMyfDD3MA2d/meXW+ZOZl7b6u/UlMTER0dLTBy+Sz+jL6nLKyskL9+vWxfft27N27F6GhodixYwdUKhVCQkKUY14XlNq1axe0Wi0aNWqkF4TJa7p917NnT/Ts2TPTvMb2XW5sx9DQUCUYpPsYTFBQkPKSYJ2//voLXbt2Vb7KaExGx66npycsLCyMTnN0dERsbKzRa4Cp2oRXaQuz2w7o+qZ5fW3ITFRUFADofeQop+3ItWvXACBbX4s25fbOSVvl7++PGTNmYPjw4RgwYAAGDBgAX19f1KlTB61atULnzp1haWmpLCO/r2FpaWnKR0Ne/HDVq/R7MpOT9mDSpEk4deoUNm/ejM2bNysfaAoODsZbb72l95X3nP4Wy4rslIMKDgalCqhq1aphyZIlOHbsmNG7mFmV3c7bqFGjsHbtWgQEBOB///sfatSoAVdXV6Vxr1u3Lg4ePJhhhz0nncXMAhPGpunuNtjb26Njx45ZXo+ZmRmWLl2K0aNHY+PGjdi/fz/279+P2bNnY/bs2WjdujXWrl2ba3eHc6vjHBgYCDMzM2i1Whw+fDhXRwBlRW7/ANDtPw8PD4SGhmaa19XV1SRlyooyZcogKCgIe/fuxeLFizFq1Cjs3r0bV69ehUaj0Rs9lR8y+pKKzsu2WXa2qW5dVapUQeXKlTPNW6tWrSwtc82aNRg3bhzs7e3x3XffoXHjxspXAlUqFUaPHo1JkyblattjCvb29ujcuTMWLFiAiIgIJCUlKV/OyczRo0fx7rvvQq1WY/LkyWjdujWKFy8OW1tbqFQqzJ07F++++26G28PGxual63Bzc0OVKlWwefNmDB48GFu3boWLi4tBPt3+rl+/vvIDISNvvPHGS9f7qooUKYKIiAgEBgaiatWqiIqKwv79+w1GeWX3mPjmm2/www8/wMPDA1999RXq1q0Ld3d3ZYRhjx49sHz58mxv87w4X/JaVo6fVxUSEoLt27dj+/btaNasGXbt2oWKFSvC3d0dwLMfqbrRU7r/hoSE5Hm50tPtu+bNmyvlyoivr69BWm5sx5EjR770y5lPnjxBu3btcO/ePfTu3Rvvv/8+SpUqBUdHR6jVapw/fx5ly5bNtfbTlG3Cq7aFr+u1ISMiguPHjwMAKlasqKSbqh0pKNt74MCB6NKlC9avX499+/Zh3759WLFiBVasWIGxY8di7969yuip/L6GnTlzBsnJyQD09+mr9nsyktP2wMPDA0eOHMGePXuwY8cO7N+/H3///Tf279+PL7/8EpMmTcLHH38MIOe/xbIiO+WggoNBqQKqVatWGDp0KB4+fIj169ejffv2Jlnvr7/+CgD45ZdfUKlSJYPpumG7uaFYsWIAnn/O2Bhj03RBGZVKhfnz52f7Ali+fHmUL18ew4cPh4hg165d6NGjBzZs2IDFixdn6QejKRUpUgRBQUHYs2cPFi1ahA4dOmRr/mLFiiEyMlK5U/SiuLg45dO5un2Sl3T7z8XFxeCz26+7Pn36YO/evViwYAFGjRqlPIrVrVs3vR8fuu0YHR2N+Ph4o6OldPsjq9tcFxjWDbt+ke5uqCno9mG9evXw3Xff5coydW3PxIkTjT5mkJttj4uLC6ysrJCUlISrV68a7YRm1i5lV0REBBYsWIANGzZArVZn+ChteitXroSIYODAgRgxYoTB9NzYHpaWlvjtt9/Qo0cPrFq1Cg0bNsSOHTuUURk6uv3dtm1bfPTRR6+83twSGBgIV1dXREVFKSMLXoXuGJwzZw7atGljMD2n2zwvzpeXKVasGC5duoTLly8bfRRF1/5YW1sb3Lk3FV2AaceOHTh+/Diio6P1zo2QkBD8+OOPiIyMzLeglI+PDyIjI9GnT598v/GQmT///BP37t1D1apVletSernZfgKmbRNM0Rampzt3THFtMGbTpk2IjY0FAL3HQXPajhQvXhznzp1DZGSk8oqBzOTX9s5JW+Xu7o6+ffuib9++AIDIyEhERETg4MGDGDlyJBYtWgQg/69hS5cuBfCs75H+tRV51e95lfZApVIhODhYCYQnJiZi4cKF6N+/P0aPHo1OnTrB39//lX+LvUxWy0EFR8G6PUAKf39/dO/eHQAwbNgwJWiQkfv372f4fHd26NZj7I7f1q1bc6Xjr1OtWjXY2triwYMHSoczvaioKGzfvt0g3cvLC5UqVcKjR4+UZ+VzSqVSoUmTJujRowcA5Mo7ZPLCJ598AgBYv379Sx+tFBHlfTnA82e6dRfnF+kuWKVLl86VoJQueKJ7Jv5FutF3Z8+eVZ6Xz2svK1NWde7cGY6Ojrhw4QJ+//13rFmzBoD+o3sA4O3trVwsjQXe0j/2l9H7Ql6k2zf//vuvwbQnT55g9+7dWa3GK2vRogWAZ8djbj0qmVnbc//+faNtQU6Zm5ujXr16AICff/7ZaJ4lS5bk2vrq16+P6tWrw8XFBR06dDB4RNaYzLZHYmIiVq9enStls7CwwIoVKxAeHo5//vkHQUFBBgFO3f7W/VjJqlc97162rocPHyqPH3h7e+doHellts3/+eefHF8f8uJ8eRldu59R4F/X7gcFBeXbuzoCAwPh4uKCU6dOYdmyZQCgN9pNF4CaN28eLly4AB8fH5QpUybLy8/K8feyPLp9p/vx+LrSHbsZPTql+1GcW3LaJuSEqdpCnYYNGwLI+NqwePHiXF1fenFxcRgyZAiAZ+dClSpVlGk5bUd07wr78ccfs5Tf1Ns7N9uqgIAAZQRN+vbalMfri44dO6YEEYcOHar3NEZO+z0va7dysz2wtrbGe++9h0qVKkGr1eLUqVMAXu23WE76BhmVgwoOBqUKsJkzZ6JUqVK4cuUK6tevrxdo0ElOTsb8+fMRGBho9Mdqdume0505c6Ze+rlz5/Dee++98vLTs7W1xTvvvAMAGDJkiPISWeDZy/kGDBiQ4fPsEyZMAAD07t0bGzZsMJguIvj777+xbds2JW3x4sU4evSoQd5Hjx4pL1o0dmF4HTRt2hTDhg0D8GxUzldffYWkpCSDfEePHkVoaCimTZumpPXt2xeOjo44duwYvvzyS70L8vHjx5VtOXz48Fwpq+7H4YULF4w+I29hYYGxY8dCRNC+fXujx3VaWhp27dqFv/76K1fL9KpBMFtbWyVYHBERgadPn6JixYqoUaOGQV7d3bgvvvgCJ0+eVNJFBBMmTMCJEyfg5OSk3OF7Gd0PtFmzZum9hyohIQH9+vXDjRs3clyv7AoMDETHjh1x48YNdOjQweid44SEBPz8889653VmdG3P3LlzlWHuwLNOelhYGOLi4nKl7DqDBw8G8Kyte/ElnFOmTMGxY8dydX2HDx9GVFRUln/c6rbHokWL9EbHJSYm4oMPPsCVK1dyrWy6F8YOGDAAFy9eRFBQEM6fP69Mb9u2LWrUqIFDhw6hd+/eRt8PERsbix9++EGvk/mytuBldB+nMHZT5u7duwgLC0NycrLyLpFXpdvms2bN0nsc9s6dO+jVq1eOg2t5cb68zKBBg2Bubo5169YZ/ADZtm0b5syZAwD5OvJNpVKhcePGEBHMmjULlpaWaNCggTK9SZMmUKlUyg+67I6Sykq7/7I8/fr1g6+vL1auXImPP/7Y6EjVu3fvZvkHf17RHbs7d+7E2bNn9abNnTsXv/zyS66uL6dtQk6Ysi0Enj0Wplar8euvvxrcBFyxYgXWrVuXq+sDnvULNm/ejJo1a+LChQvw9PQ0OKZy2o4MHToUDg4OWL9+PT799FODtvj+/ft6/TBTb++ctFW7du3Cpk2bDOoiIvj9998B6PfnTXm86jx9+hSzZ89GcHAwEhMTERwcbNDe5rTfo2u3XjzXX1xudtuDadOmGX0HVWRkpDK6Kv12zclvsfTlz6jdzW45qIDIy0/7Ud67d++eBAcHK58dLVGihLRt21a6d+8ujRs3Fnt7ewEgjo6Oep9JftmnkDP6LO/q1atFpVIJAKlYsaJ069ZNGjduLBYWFtK4cWOpW7eu0c945vRz9Y8ePZJq1aoJALG3t5c2bdpIly5dxMvLS1xdXZXPU0+cONFgmd98842Ym5sLAClVqpS8+eab0qNHD2natKnyueT0n3vXfcbXy8tLWrZsKW+99Za0bNlSNBqNAJAKFSpk+JldY3T75EW6z/5m9IlYXZ2y8lngF02cOFEsLCyUT6KHhIRIjx49pE2bNuLn56eU6cXP3G/YsEGsra0FgAQEBEj37t2lSZMmyvbr3bu3wbpyegyJiFSvXl0ASNmyZeWtt96SPn36GJRp+PDhSnnfeOMNadu2rXTr1k2Cg4PFyclJAMjs2bP15slom+tkdBz+/vvvAkAsLS2lVatWEhERIX369JH9+/dnuKyMHDp0SCkHAPn666+N5tNqtdKzZ08BIObm5tKkSRPp3r27lC1bVgCIjY2NbNq0Kct1SE5OVrarRqORN998U1q0aCFFixaVYsWKSUREhNH99bL9+LLjMaPyxMfHS5MmTZTtWqNGDenSpYt07txZatSoIZaWlgJA/v33X6PLfdHly5eV/V6sWDHp2LGjtGnTRjQajXh6eua4fpkdp/379xcAYmZmJsHBwdK9e3d54403xMzMTAYNGpSjT5frjosbN25kKb+ufP7+/nrpsbGxSlvi4uIi7dq1k44dO4qbm5s4ODgo5Xvxk9BZ+VS07lPWxj5prvvct7u7u5w6dUpJv3XrllSpUkX55HfdunWlW7du0qFDB6lSpYqo1WoBIE+fPtVbXlbagozo2ma1Wi1VqlSRjh07SteuXaV+/fpKO+js7CwHDx7M1jbIqP5//fWXctyWKlVKunTpIs2bNxcbGxt54403pH379kbPlay06bl9voi8/Lo7Z84cMTMzEwBStWpV6dGjh9SrV0+5xo8bN85gnle5PhmjOz8zOo/mzJmjnDONGjUymB4YGKhM//nnn40uI6PtcPfuXbGzsxMAUq9ePQkPD5c+ffrI/PnzlTxZuTacOXNGub46OTlJgwYNpEePHtKuXTspX768qFQqcXd3N1rvjNqlrNDVO6P9+yJdH8fS0lKaNWsm3bp1k4CAAFGpVPLJJ58YPeYzawt0MurT5KRNyKw9zkhetYWZ1X3KlCnK9q9Vq5b06NFDatSoIQBkyJAhL91mxujqUK9ePQkLC5OwsDDp1q2bhISEiLOzs7K+4OBguXz5stFl5LQd2bp1qzg4OChte7t27aRz585Ss2ZNsbCw0NtG+bG9s9tWzZgxQ/ntExwcLD169JD27dsr5dZoNHL8+HG9eXJ6DcuIrj4ApGPHjso+7dSpk9StW1fpc5uZmcl7770njx8/NlhGTvs9SUlJ4uXlJQAkMDBQevXqJX369JEpU6YoeXLSHuiuuQEBAdK+fXvp0aOHBAcHK78VevXqZVCH7P4WE3l5u5uTctDrj0GpQmLz5s3Sq1cvKVWqlNjb24uFhYV4eHhI06ZN5euvv5bo6Gi9/K/yQ+3PP/+UJk2aiKurq9ja2kqFChVk4sSJkpSUlGHnL6dBKZFnganRo0dLyZIlxdLSUjw8PKRnz55y7do1pUGeM2eO0eWePn1a+vXrJ6VLlxZra2uxtbWVkiVLSmhoqHz77bdy69YtvXoNHjxYatasKR4eHsq66tSpIzNnzjR6wchMfgSlRESuXr0qo0aNkho1aoiLi4uYm5uLRqORwMBAGTRokBw7dszofGfPnpWwsDDx9vYWCwsLcXJykkaNGsmKFSuM5n+VY+jatWvSo0cP8fT0VC4ixjoi+/fvl7feekt8fX3FyspKHBwcpEyZMtKuXTv56aefJCYmRi9/ToNSIiI//vijVK1aVWxtbZXl5HQfVKxYUbmgRkVFZZp32bJlSqDNwsJCfHx8JDw8XCIjI7Ndh9jYWBkwYICyD4sVKyb9+vWTe/fuZbi/8iooJSKSlpYmy5Ytk5YtW4q7u7tYWFiIi4uLVKhQQXr37i1r166V5OTkTLaOvitXrshbb70lxYsXFysrK/H19ZX33ntP7t69m+P6vexH0Pz586VatWpibW0tGo1GQkJCZPfu3Tn68SSSe0EpEZEHDx7IBx98IP7+/mJlZSVeXl7y9ttvy4ULFzL8AfCqQSkRkUmTJgkAKVKkiN7NjsTERPnhhx+kUaNGStvj5uYmVapUkf79+8vWrVsNlpXVtsCY06dPy4wZM6R169YSEBAgTk5OYm5uLs7OzlK3bl0ZP368PHjwwGC+V/lxdOrUKWnTpo14enqKtbW1lC5dWkaMGCHx8fEZnitZbdNz+3x52XVX5FmgrVOnTuLh4SHm5ubi4uIib775pmzbts1oflMHpS5duqScM8ZuPuluXqhUKrl7967RZWS2Hf78808JCQmRIkWKKD96XzwusnJtiI+PlylTpkidOnWUttzT01Nq1Kghw4cPlwMHDhittymDUsnJyTJ16lSpWLGi2NrairOzszRr1ky2bduW4TH/KkEpkey3CTltV/OiLXxZ3X/77TepX7++2NnZib29vdStW1dWrVqVpW1mjG47pv9nZ2cnXl5e0rBhQxk2bJgcOnTopcvJaTty7do1GTRokJQtW1asra3F3t5eypQpIxEREQaB/fzY3tlpqy5evCjjxo2TJk2aSPHixcXa2lqKFCkilSpVkpEjR2Z4/c3JNSwj6YNSun9mZmbi6Ogofn5+0qpVK5k4caJcu3btpcvJbr9H5Nn1sU2bNlK0aFGlbUt/XuWkPVi6dKn07t1bKlSoIM7Ozkp5WrRoIWvXrhWtVmu0Dtn5LaaTWbub03LQ600lYuKHZ4lySUpKCipUqIDz58/j6NGjqFq1an4XiYiIiIiIiIiyiO+Uotfe0aNHDT5n//jxYwwYMADnz59HpUqVGJAiIiIiIiIiKmA4Uopee35+fnjy5AkqVqwINzc33L9/HydOnEBMTAycnZ2xY8cOBAYG5ncxiYiIiIiIiCgbGJSi1963336LtWvXIjIyErGxsTAzM4Ovry+aNWuGjz76CD4+PvldRCIiIiIiIiLKJgaliIiIiIiIiIjI5PhOKSIiIiIiIiIiMjkGpYiIiIiIiIiIyOQYlCIiIiIiIiIiIpNjUIqIiIiIiIiIiEyOQSkiIiIiIiIiIjI5BqWIiIiIiIiIiMjkGJQiIiIiIiIiIiKTY1CKiIiIiIiIiIhMjkEpIiIiIiIiIiIyOQaliIiIiIiIiIjI5BiUIiIiIiIiIiIik2NQioiIiIiIiIiITI5BKSIiIiIiIiIiMjkGpYiIiIiIiIiIyOQYlCIiIiIiIiIiIpNjUIqIiIiIiIiIiEyOQSkiIiIiIiIiIjI5BqWIiIiIiIiIiMjkGJQiIiIiIiIiIiKTY1CKiIiIiIiIiIhMjkEpIiIiIiIiIiIyOQaliIiIiIiIiIjI5BiUIiIiIiIiIiIik2NQioiIiIiIiIiITI5BKSIiIiIiIiIiMjkGpYiIiIiIiIiIyOQYlCIiIiIiIiIiIpNjUIqIiIiIiIiIiEyOQSkiIiIiIiIiIjI5BqWIiIiIiIiIiMjkGJQiIiIiIiIiIiKTY1CKiIiIiIiIiIhMjkEpIiIiIiIiIiIyOQaliIiIiIiIiIjI5BiUIiIiIiIiIiIik2NQioiIiIiIiIiITI5BKSIiIiIiIiIiMjkGpYiIiIiIiIiIyOQYlCIiIiIiIiIiIpNjUIqIiIiIiIiIiEyOQSkiIiIiIiIiIjI5BqWIiIiIiIiIiMjkGJQiIiIiIiIiIiKTY1CKiIiIiIiIiIhMjkEpIiIiIiIiIiIyOQaliIiIiIiIiIjI5BiUIiIiIiIiIiIik2NQioiIiIiIiIiITI5BKSIiIiIiIiIiMjkGpYiIiIiIiIiIyOQYlCIiIiIiIiIiIpNjUIqIiIiIiIiIiEyOQSkiIiIiIiIiIjI5BqWIiIiIiIiIiMjkGJQiIiIiIiIiIiKTY1CKiIiIiIiIiIhMjkEpIiIiIiIiIiIyOQaliIiIiIiIiIjI5BiUIiIiIiIiIiIik2NQioiIiIiIiIiITI5BKSIiIiIiIiIiMjkGpYiIiIiIiIiIyOQYlCIiIiIiIiIiIpNjUIqIiIiIiIiIiEyOQSkiIiIiIiIiIjI5BqWI8tDVq1ehUqkwbdq0/C4KFSDBwcEIDg7O72LkuXHjxkGlUiEqKiq/i5Lnfv31Vzg7O+Px48e5srwtW7bA3t4eDx48yJXlEdF/B/smlNeCg4NRoUKF/C5GpgrzeaBSqTBgwID8Lkae02q1qFChAiZOnJhry6xduzZGjBiRa8ujrGFQigqkhQsXQqVSKf+sra3h5eWF0NBQfPvtt3j06FF+F7HA0l2kdf8sLCzg6uqKunXrYvTo0bh+/XqOl3379m2MGzcOJ06cyL0Cv4JNmzZh3LhxOZ5/zZo1UKlU+OmnnzLMs337dqhUKnz77bc5Xk9Bk5aWhgULFiA4OBjOzs6wsrKCn58fevfujSNHjuR38UwuLS0NY8eOxcCBA2Fvb6+kz5kzByVKlICzszN69uyJ+Ph4vfm0Wi0CAwPx5ZdfGiyzefPmKFWqFCZNmpTn5SeirGHfJO+wb5J9um31zjvvGJ3+ySefKHle55tDZ8+exbhx43D16tUsz7Nv3z60aNECxYoVg7W1NYoXL47WrVtj2bJleVdQE7h06RLeffddlCxZEtbW1nB0dES9evXwzTff4OnTp/ldPJNbvnw5bty4oReAu3XrFt588004OjqifPny2LBhg8F8a9asgZubG+Li4gymffzxx5g1axbu3r2bp2UnfQxKUYH2+eefY8mSJZg9ezYGDhwIABg8eDAqVqyIU6dO5XPpCrbu3btjyZIlmDdvHsaMGYOSJUvi66+/Rrly5bBixYocLfP27dsYP378a9XxGz9+fI7nf/PNN6HRaDLt5CxbtgxqtRrdunXL8XoKkqdPn6JVq1aIiIiAiGD06NGYPXs2evXqhYMHD6JmzZq4efNmfhfTpDZs2IBz586hX79+Stq+ffvw/vvvo23bthg3bhx27NiB4cOH6833448/Ii4uDsOGDTO63HfffRdz5szhD12i1wz7JnmHfZPssba2xurVq5GcnGwwbfny5bC2ts6V9eSls2fPYvz48VkOSq1cuRINGjTAvXv3MGjQIMycORNvv/02YmNj8eOPP+ZtYfPQxo0bUbFiRfz6669o3bo1Zs6ciUmTJqF48eIYPnw4Bg0alN9FNLmpU6eiW7du0Gg0SlpYWBguX76MyZMno2rVqujcubPesZOYmIiPPvoIEyZM0JtPp23btnB0dMT3339viiqQjhAVQAsWLBAAcvjwYYNpO3fuFBsbG/H19ZUnT57kQ+meu3LligCQqVOn5ms5siOzMl+9elXKlCkjlpaWcuLEiWwv+/DhwwJAFixYkAslfXX9+/eXV20G+/TpI2ZmZnLr1i2DaU+fPhWNRiPNmzfP1jIbNmwoDRs2fKVy5RfdNp0xY4bBtNTUVJk6darcuHFDRETGjh0rAOTBgwcmLqVptWnTRurXr6+X9vHHH0ujRo2UvxcsWCAeHh7K37GxseLq6iqrV6/OcLn37t0TtVot8+bNy/1CE1G2sW+Sd9g3yT4A0q5dOzEzM5N169bpTdu/f78AkI4dO+bqdfjx48ci8qwf88Ybb+TKMleuXCkAZPfu3VnKX758eXnjjTckKSnJYNq9e/eU/zfVeaDbJq/i8uXLYm9vLwEBAXL79m2D6RcuXJCvv/5a+RuA9O/f/5XX+zo7duyYAJAdO3YoaU+ePBGVSiV79uwRERGtVislSpSQH374QcnzxRdfSJUqVSQtLS3DZQ8YMEB8fX1Fq9XmXQVID0dKUaHTuHFjjBkzBteuXcPSpUv1pkVGRqJTp05wdnaGtbU1qlevjvXr1xss4+HDhxgyZAj8/PxgZWUFb29v9OrVSxnenJycjM8++wzVqlWDRqOBnZ0dgoKCsHv37gzLNXfuXPj7+8PKygo1atTA4cOHDfLs2rULQUFBsLOzg5OTE9q2bYt///1XL8+jR48wePBgpWxubm5o2rQpjh07ppfv77//RvPmzaHRaGBra4uGDRti//79Wd6Oxvj6+mLhwoVITk7GlClTlPSYmBh89NFHqFixIuzt7eHo6IgWLVrg5MmTSp4//vgDNWrUAAD07t1bGTK+cOFCAMDevXvRuXNnFC9eHFZWVvDx8cGQIUMMhiPfvXsXvXv3hre3N6ysrODp6Ym2bdsa3EHbvHmzsi0dHBzw5ptv4p9//lGmh4eHY9asWQCg90iAzp07dxAZGYmUlJRMt8nbb78NrVZr9A7txo0bERcXh7feegsAkJqaii+++EI5Dvz8/DB69GgkJSVlug7dIyEv1vGPP/6ASqXCH3/8oaTp3uNw6tQpNGzYELa2tihVqhRWrVoFANizZw9q1aoFGxsblC1bFjt27DBY361btxAREQF3d3dYWVnhjTfewPz58zMtIwDcvHkTc+bMQdOmTTF48GCD6Wq1Gh999BG8vb310h8+fIjw8HA4OTlBo9Ggd+/eePLkiV6eBQsWoHHjxnBzc4OVlRXKly+P2bNnG6zDz88PrVq1wr59+1CzZk1YW1ujZMmSWLx4sUFe3TaysbGBt7c3JkyYgAULFhjd1i87njKSmJiILVu2ICQkRC/96dOnKFKkiPK3s7OzXp3HjRuHihUrokOHDhku283NDZUqVcJvv/320nIQUf5i3+QZ9k1M0zfRKVasGBo0aGAwovvnn39GxYoVjb73Kat1Dg8Ph729PS5duoSWLVvCwcFB6e8Ys23bNtja2qJ79+5ITU0F8PJjf+HChejcuTMAoFGjRsr2SN/vedGlS5dQo0YNWFpaGkxzc3MzOs/LzoNTp04hPDxceWzOw8MDERERiI6O1sune1fm2bNn0aNHDxQpUgT169dXpi9duhTVqlWDjY0NnJ2d0a1bN9y4cSPDuuhMmTIFjx8/xrx58+Dp6WkwvVSpUkZHSq1btw4VKlRQ+nJbtmzRm37t2jV88MEHKFu2LGxsbODi4mIwsgh43g/dv38/hg4diqJFi8LOzg7t27c3eLelVqvFuHHj4OXlBVtbWzRq1Ahnz56Fn58fwsPD9fI+fPgQgwcPho+PD6ysrFCqVClMnjwZWq32pdtk3bp1sLS0RIMGDZS0xMREiIjSv1KpVHByclL6V7du3cL//vc/fPPNNzAzyzgM0rRpU1y7du21GT35n5DfUTGinMjsbqSIyI0bNwSAdOrUSUk7c+aMaDQaKV++vEyePFm+++47adCggahUKlmzZo2S79GjR1KhQgVRq9XSt29fmT17tnzxxRdSo0YNOX78uIiIPHjwQDw9PWXo0KEye/ZsmTJlipQtW1YsLCyUPCLP78IEBgZKqVKlZPLkyTJlyhRxdXUVb29vSU5OVvJu375dzM3NpUyZMjJlyhQZP368uLq6SpEiReTKlStKvh49eoilpaUMHTpUfvrpJ5k8ebK0bt1ali5dquTZuXOnWFpaSp06dWT69OkyY8YMqVSpklhaWsrff/+d6bbNyp0jf39/KVq0qPL34cOHxd/fX0aOHClz5syRzz//XIoVKyYajUYZQXT37l35/PPPBYD069dPlixZIkuWLJFLly6JiMjAgQOlZcuW8uWXX8qcOXOkT58+olar9fahiEjdunVFo9HIp59+Kj/99JN8+eWX0qhRI+WuiIjI4sWLRaVSSfPmzWXmzJkyefJk8fPzEycnJ2VbHjhwQJo2bSoAlLIsWbJEWUZYWJgA0Nv2xqSlpYm3t7dUq1bNYFqHDh3E1tZWHj16pLfMTp06yaxZs6RXr17Kncz0XhwppTveXyzL7t27De4eNmzYULy8vMTHx0eGDx8uM2fOlPLly4tarZYVK1aIh4eHjBs3Tr7++mtlH8XHxyvz3717V7y9vcXHx0c+//xzmT17trRp0ybD0U/pzZ07VwDI4sWLM82noxspFRgYKB06dJDvv/9e3nnnHQEgI0aM0Mtbo0YNCQ8PlxkzZsjMmTOlWbNmAkC+++47vXy+vr5StmxZcXd3l9GjR8t3330nVatWFZVKJWfOnFHy3bx5U5ydncXFxUXGjx8v06ZNk4CAAKlcubLBts7K8ZSRffv2CQBZv369XvqSJUvE1tZWtm7dKufPn5cGDRpISEiIiIj8888/YmVlJSdPnnzpNnznnXfE1dX1pfmIKO+xb8K+yevSNxF5Plpm7ty5YmNjo/RFUlJSpGjRojJp0iSjI5azWuewsDCxsrISf39/CQsLkx9++EG5/r84UmrDhg1iZWUlvXr1ktTUVBHJ2rF/6dIl+fDDDwWAjB49Wtked+/ezbDeZcqUER8fH2VUdkaycx5MmzZNgoKC5PPPP5e5c+fKoEGDxMbGRmrWrKk3mka3PcuXLy9t27aV77//XmbNmiUiIhMmTBCVSiVdu3aV77//XjmX/Pz8JDY2NtOyFitWTEqWLJlpnvQASOXKlcXT01O++OIL+frrr6VkyZJia2srUVFRSr6VK1dK5cqV5bPPPpO5c+fK6NGjpUiRIuLr6ysJCQlKPl3bFhgYKI0bN5aZM2fKsGHDRK1WS5cuXfTWPWLECAEgrVu3lu+++0769u0r3t7e4urqKmFhYUq+hIQEqVSpkri4uMjo0aPlhx9+kF69eolKpZJBgwa9tI4hISFStWpVg3R/f3/p1q2bXL58WZYuXSoqlUr27dsnIs/aqRePY2Nu3rwpAGTmzJkvzUu5g0EpKpBe1vETEdFoNBIYGKj83aRJE6lYsaIkJiYqaVqtVurWrSulS5dW0j777DMBoNcZTJ9f5NljSC8OC46NjRV3d3eJiIhQ0nQXPBcXF4mJiVHSf/vtNwEgGzZsUNKqVKkibm5uEh0draSdPHlSzMzMpFevXnr1ymxIrlarldKlS0toaKjehfLJkydSokQJadq0aYbzpi9zZh2/tm3bCgCJi4sTEZHExESDYbBXrlwRKysr+fzzz5W0zIbIG3ucYdKkSaJSqeTatWsi8mwbv6xsjx49EicnJ+nbt69e+t27d0Wj0eilZzZEPjsdv+HDhwsAOXfunJIWFxcn1tbW0r17dxEROXHihACQd955R2/ejz76SADIrl27lLRXDUoBkGXLlilpkZGRAkDMzMzkr7/+UtK3bt1qsD/69Okjnp6eep0WEZFu3bqJRqPJ9LGTIUOGCAC9Hz+Z0XXe0p8zIiLt27cXFxcXvTRj6w0NDTXopPn6+goA+fPPP5W0+/fvi5WVlQwbNkxJGzhwoKhUKr2yRkdHi7Ozs962zs7xZMxPP/0kAOT06dN66ampqdKhQwcBIADEx8dHTp06JSIizZo1k/feey/T5ep8+eWXAkDvkQQiyh/sm7BvkpH86JvoglIxMTFiaWmpBLc2btwoKpVKrl69ajQolZU6py/LyJEjDfKnD0qtXr1aLCwspG/fvnr7I6vHfnYf35s3b54AEEtLS2nUqJGMGTNG9u7da/RYyOp5YGybLF++3KC/odueur6fztWrV0WtVsvEiRP10k+fPi3m5uYG6enFxcUJAGnbtm2W6i8iSv0vXryopJ08edIg0GKsXgcPHjS4wahr20JCQvTO3yFDhoharZaHDx+KyLPj2dzc3OBm67hx4wSAXlDqiy++EDs7Ozl//rxe3pEjR4parZbr169nWkdvb2/p2LGjQfrOnTulSJEiSv9q8ODBIvLskVUbGxu5evVqpsvVsbS0lPfffz9LeenV8fE9KrTs7e2VFwDHxMRg165d6NKlCx49eoSoqChERUUhOjoaoaGhuHDhAm7dugUAWL16NSpXroz27dsbLFM3hFqtVivDgrVaLWJiYpCamorq1asbDFUHgK5du+o9qhMUFAQAuHz5MoBnw7FPnDiB8PBwODs7K/kqVaqEpk2bYtOmTUqak5MT/v77b9y+fdtovU+cOIELFy6gR48eiI6OVuqakJCAJk2a4M8//8zSsNjM6L4gptu+VlZWyjDYtLQ0REdHw97eHmXLljW6PYyxsbFR/j8hIQFRUVGoW7cuRATHjx9X8lhaWuKPP/5AbGys0eVs374dDx8+RPfu3ZW6R0VFQa1Wo1atWpk+xpDewoULISLw8/N7ad63334bAPSGx69evRqJiYnKUHbdPhw6dKjevLqXWG/cuDFL5coKe3t7vRerly1bFk5OTihXrhxq1aqlpOv+X3ccighWr16N1q1bQ0T0tl9oaCji4uIy3Z+6r8c5ODhkq7zvvfee3t9BQUGIjo7W+xpd+uMjLi4OUVFRaNiwIS5fvmzw9ZTy5csr5xgAFC1aFGXLllXqCQBbtmxBnTp1UKVKFSXN2dnZ4NGDVz2edEP705//wLM2ZPXq1bhw4QKOHDmC8+fPo2LFili/fj0OHTqEL774Ardu3ULr1q3h5eWF1q1bGz3ndct9nb+cRETPsW/Cvomp+iY6RYoUQfPmzbF8+XIAz/oqdevWha+vb47rnN7777+f4bqXL1+Orl27Kh/m0O2P7Bz72RUREYEtW7YgODgY+/btwxdffIGgoCCULl0aBw4cMMj/svMA0N8miYmJiIqKQu3atQHA6LH0Yr9mzZo10Gq16NKli97+9/DwQOnSpTPd/zntW4WEhMDf31/5u1KlSnB0dMywXikpKYiOjkapUqXg5ORktF79+vXTe5w0KCgIaWlpuHbtGgBg586dSE1NxQcffKA3n+6DD+mtXLkSQUFBKFKkiN42CQkJQVpaGv78889M6xcdHW3QtwKePSp9/fp1/PXXX7h+/TpmzJgBrVaLDz/8EMOGDYOvry9mz56NgIAAlC1bFj/88IPR5evKRaZhnt8FIMorjx8/Vp4dv3jxIkQEY8aMwZgxY4zmv3//PooVK4ZLly6hY8eOL13+okWLMH36dINn+0uUKGGQt3jx4np/6xpRXedF15iXLVvWYN5y5cph69atSEhIgJ2dHaZMmYKwsDD4+PigWrVqaNmyJXr16oWSJUsCAC5cuADg2dcnMhIXF2e0Ic+qx48fA3h+gdRqtfjmm2/w/fff48qVK0hLS1Pyuri4ZGmZ169fx2effYb169cbdOp0QQcrKytMnjwZw4YNg7u7O2rXro1WrVqhV69e8PDwAPC8/o0bNza6HkdHx2zUNGsqVaqEChUqYPny5cpnnJctWwZXV1eEhoYCeLaPzczMUKpUKb15PTw84OTkpBwDucHb21uv0wAAGo0GPj4+BmnA8+PwwYMHePjwIebOnYu5c+caXfb9+/czXK9u22b3a3CZnR+6Ze7fvx9jx47FwYMHDd43FRcXp/cFlReXp1tm+uPq2rVrqFOnjkG+F/dPbh1PImI0Pf36kpOTMWzYMIwdOxaurq4ICgqCp6cnNmzYgP/973/o0aOHwXs0dMt9cX8T0euJfRP2TYzJi75Jej169EDPnj1x/fp1rFu3Tu/dWy/KSp11zM3NDd4TqXPlyhW8/fbb6Ny5M2bOnKk3LTvHfk6EhoYiNDQUT548wdGjR/HLL7/ghx9+QKtWrRAZGan3bqmXnQfAsyDa+PHjsWLFCoN+0IvbBDA83y5cuAARQenSpY2W18LCIsO65FbfCjDsCz19+hSTJk3CggULcOvWLb2+irF6ZbXNeLEv5ezsbHBuX7hwAadOnULRokWNlj+z/qZORn0re3t7vZuwCxYswN27dzFy5Ejla8dLly6FSqVCjx49ULZsWTRq1Mhg2exbmQ6DUlQo3bx5E3FxcUqjqLv79tFHHylBghe92IBmZunSpQgPD0e7du0wfPhwuLm5Qa1WY9KkSbh06ZJBfrVabXQ5GTWmmenSpQuCgoKwdu1abNu2DVOnTsXkyZOxZs0atGjRQqnr1KlT9UaBpKe7m5hTZ86cgZubm3Kh/PLLLzFmzBhERETgiy++gLOzM8zMzDB48OAs3flMS0tD06ZNERMTg48//hgBAQGws7PDrVu3EB4erreMwYMHo3Xr1li3bh22bt2KMWPGYNKkSdi1axcCAwOVvEuWLFE6g+mZm+dNs/f2229j5MiROHLkCLy9vbF79268++67BuvLyQUuo3nSd7DTy+h4e9lxqNt2b7/9doY/HCpVqpRhOQMCAgAAp0+fzvDYy0m5Ll26hCZNmiAgIABfffUVfHx8YGlpiU2bNil3wLKzvOx41eNJ98MnNjY2w467zowZM2Bubo4BAwbgxo0b2LdvH65cuQI/Pz9MmTIFJUuWxM2bN/WWo+sIurq6ZqteRGR67Juwb2LqvolOmzZtYGVlhbCwMCQlJaFLly5G82WnzoD+aLQXeXp6wtPTE5s2bcKRI0dQvXp1ZVpuH/sZsbW1RVBQEIKCguDq6orx48dj8+bNen2crJwHXbp0wYEDBzB8+HBUqVIF9vb20Gq1aN68udFjKf0IJOBZfVUqFTZv3mx0fZkd+46OjvDy8sKZM2deWt/0slKvgQMHYsGCBRg8eDDq1KkDjUYDlUqFbt26Ga1XbvevmjZtihEjRhidXqZMmUznd3FxyXBkYnrx8fH45JNPMG3aNNjZ2WH58uXo1KkT2rVrBwDo1KkTfv75Z4Og1MOHD9m3MiEGpahQWrJkCQAoFzrdnToLCwuDr2C9yN/f/6UN/6pVq1CyZEmsWbNGL2AwduzYHJVXN4T63LlzBtMiIyPh6uoKOzs7Jc3T0xMffPABPvjgA9y/fx9Vq1bFxIkT0aJFC2WorqOj40vrmhMHDx7EpUuXlEfWgGfbo1GjRpg3b55e3hcb9IyCK6dPn8b58+exaNEi9OrVS0nfvn270fz+/v4YNmwYhg0bhgsXLqBKlSqYPn06li5dqtTfzc3tpfXPzTsg3bt3x6hRo7Bs2TL4+voiLS1N71EwX19faLVaXLhwAeXKlVPS7927h4cPH2Y4jB54fifq4cOHeum5OboKePaYm4ODA9LS0nJ07LRo0QJqtRpLly5Fz549c61cGzZsQFJSEtavX693ly6rjzsY4+vri4sXLxqkv5iWnePJGF2g7sqVK6hYsWKG+e7cuYMJEyZg5cqVMDc3Vx6B8fLy0vvvrVu39IJSV65cgaura4Z3Gono9cG+Cfsmpu6b6NjY2KBdu3ZYunQpWrRokeGP7ezWOTPW1tb4/fff0bhxYzRv3hx79uzBG2+8ASB7x35ubQ9dUOzOnTvZmi82NhY7d+7E+PHj8dlnnynputFvWeHv7w8RQYkSJV4abDGmVatWmDt3Lg4ePGh0lHdOrVq1CmFhYZg+fbqSlpiYaNDfzCpdm3Hx4kW90WLR0dEGASR/f388fvw4x+1BQEAArly58tJ8n3/+OUqUKKH0yW/fvo3AwEBlupeXl8FX9m7duoXk5GS9/jrlLb5TigqdXbt24YsvvtBrgNzc3BAcHIw5c+YYvRil/5xpx44dcfLkSaxdu9Ygn+5OgO5OQfo7A3///TcOHjyYozJ7enqiSpUqWLRokd6F4MyZM9i2bRtatmwJ4NkdrBeH07q5ucHLywtJSUkAgGrVqsHf3x/Tpk1ThrJnVNfsunbtGsLDw2FpaYnhw4cr6Wq12uAuycqVKw3eB6DrvL54sTO2PUUE33zzjV6+J0+eIDExUS/N398fDg4OSv1DQ0Ph6OiIL7/80ugnk9PXP6PyANn/7HLx4sURFBSEX375BUuXLkWJEiVQt25dZbpuH3799dd683311VcAgDfffDPDZes6s+mfr09LS8vwEbucUqvV6NixI1avXm30x8/Ljh0fHx/07dsX27ZtMxiqDzy7KzZ9+nTcvHkz2+UCYDCsfMGCBdlaTnqhoaE4ePCgXkckJiYGP//8s0G+rB5PxlSrVg2WlpY4cuRIpvlGjhyJBg0aoHnz5gAAd3d3AM9++AFQPr/+4h32o0eP5moHlYjyBvsm7JvkR98kvY8++ghjx47N8HE5IOt1ziqNRoOtW7fCzc0NTZs2VUbsZefYz2x7GLNz506j6bp3oBl7HDUzxrYJYNify0yHDh2gVqsxfvx4g+WIiPL+yYyMGDECdnZ2eOedd3Dv3j2D6ZcuXcrRPjJ2jsycOTPDkfgv06RJE5ibm2P27Nl66d99951B3i5duuDgwYPYunWrwbSHDx8iNTU103XVqVMHZ86cUc4xY86fP4/vvvsO33zzjRLcdHd3V/pWwLP+lbG+FQC9fjzlLY6UogJt8+bNiIyMRGpqKu7du4ddu3Zh+/bt8PX1xfr162Ftba3knTVrFurXr4+KFSuib9++KFmyJO7du4eDBw/i5s2bOHnyJABg+PDhWLVqFTp37oyIiAhUq1YNMTExWL9+PX744QdUrlwZrVq1wpo1a9C+fXu8+eabuHLlCn744QeUL1/eaGcrK6ZOnYoWLVqgTp066NOnD54+fYqZM2dCo9Eo7yl69OgRvL290alTJ1SuXBn29vbYsWMHDh8+rNzlMDMzw08//YQWLVrgjTfeQO/evVGsWDHcunULu3fvhqOjIzZs2PDS8hw7dgxLly6FVqvFw4cPcfjwYaxevRoqlQpLlizRe4yrVatW+Pzzz9G7d2/UrVsXp0+fxs8//6zcCdPx9/eHk5MTfvjhBzg4OMDOzg61atVCQEAA/P398dFHH+HWrVtwdHTE6tWrDe6qnD9/Hk2aNEGXLl1Qvnx5mJubY+3atbh3757yYm9HR0fMnj0bPXv2RNWqVdGtWzcULVoU169fx8aNG1GvXj3l4litWjUAwIcffojQ0FCo1WplOaNGjcKiRYuUx6ey4u2330a/fv1w+/ZtfPLJJ3rTKleujLCwMMydOxcPHz5Ew4YNcejQISxatAjt2rUzGDac3htvvIHatWtj1KhRiImJgbOzM1asWPHSC3ZO/O9//8Pu3btRq1Yt9O3bF+XLl0dMTAyOHTuGHTt2ICYmJtP5p0+fjkuXLuHDDz/EmjVr0KpVKxQpUgTXr1/HypUrERkZqfcS9qxo1qwZLC0t0bp1a7z77rt4/PgxfvzxR7i5uWX7jqfOiBEjsHTpUjRt2hQDBw6EnZ0dfvrpJxQvXhwxMTFK5yU7x5Mx1tbWaNasGXbs2IHPP//caJ5Dhw7hl19+walTp5Q0Pz8/VK9eHeHh4ejTpw9++ukn1KpVS29E3f3793Hq1Cn0798/R9uAiPIG+ybsm7xOfROdypUro3LlypnmyWqds8PV1RXbt29H/fr1ERISgn379qFYsWJZPvarVKkCtVqNyZMnIy4uDlZWVmjcuLHee6HSa9u2LUqUKIHWrVvD398fCQkJ2LFjBzZs2IAaNWqgdevW2Sq/o6MjGjRogClTpiAlJQXFihXDtm3bsjRKR8ff3x8TJkzAqFGjcPXqVbRr1w4ODg64cuUK1q5di379+uGjjz7KdP5ly5aha9euKFeuHHr16oUKFSogOTkZBw4cwMqVKxEeHp6tegHPzpElS5ZAo9GgfPnyOHjwIHbs2JHld669yN3dHYMGDcL06dPRpk0bNG/eHCdPnsTmzZvh6uqqN+pt+PDhWL9+PVq1aoXw8HBUq1YNCQkJOH36NFatWoWrV69m+vhc27Zt8cUXX2DPnj1o1qyZ0TxDhgxB165dUbNmTSWtU6dOaNu2LUaPHg3g2Wj833//XW++7du3o3jx4nojqiiP5dVn/Yjyku7TpLp/lpaW4uHhIU2bNpVvvvlG4uPjjc536dIl6dWrl3h4eIiFhYUUK1ZMWrVqJatWrdLLFx0dLQMGDJBixYqJpaWleHt7S1hYmERFRYnIs0/Wfvnll+Lr6ytWVlYSGBgov//+u4SFhYmvr6+ynMw+YQxAxo4dq5e2Y8cOqVevntjY2Iijo6O0bt1azp49q0xPSkqS4cOHS+XKlcXBwUHs7OykcuXK8v333xss//jx49KhQwdxcXERKysr8fX1lS5dusjOnTsz3ba6Muv+mZubi7Ozs9SqVUtGjRql9zlgncTERBk2bJh4enqKjY2N1KtXTw4ePCgNGzaUhg0b6uX97bffpHz58mJubq73CeazZ89KSEiI2Nvbi6urq/Tt21f5fK0uT1RUlPTv318CAgLEzs5ONBqN1KpVS3799VeDMu3evVtCQ0NFo9GItbW1+Pv7S3h4uBw5ckTJk5qaKgMHDpSiRYuKSqXS+wRzdj67rBMTEyNWVlYCQG+/6aSkpMj48eOlRIkSYmFhIT4+PjJq1Ci9zyGLiNHtdunSJQkJCRErKytxd3eX0aNHy/bt2w0+k5z+M8zp+fr6yptvvmmQjv//ZHR69+7dk/79+4uPj49YWFiIh4eHNGnSRObOnZul7ZCamio//fSTBAUFiUajEQsLC/H19ZXevXvL8ePHlXzGPkUt8vz8Tr/t169fL5UqVRJra2vx8/OTyZMny/z58w3yZVRPY9v0+PHjEhQUJFZWVuLt7S2TJk2Sb7/9VgDI3bt39fJm5XjKyJo1a0SlUhn9vLFWq5VatWrJ0KFDDaZdvHhRGjRoIPb29tKgQQO5dOmS3vTZs2eLra1thu0dEZkW+ybsm7xOfRNj1/cXGbsOZ6XOurLY2dkZXa6xvsjFixfF09NTypUrp6wvq8f+jz/+KCVLlhS1Wm3Q73nR8uXLpVu3buLv7y82NjZibW0t5cuXl08++UTvHMzOeXDz5k1p3769ODk5iUajkc6dO8vt27cN8mXUr9FZvXq11K9fX+zs7MTOzk4CAgKkf//+cu7cuQzrk9758+elb9++4ufnJ5aWluLg4CD16tWTmTNn6vUlM9r3vr6+EhYWpvwdGxsrvXv3FldXV7G3t5fQ0FCJjIw0yKdr2w4fPqy3vN27dxvsj9TUVBkzZox4eHiIjY2NNG7cWP79919xcXGR9957T2/+R48eyahRo6RUqVJiaWkprq6uUrduXZk2bZokJye/dHtUqlRJ+vTpY3Taxo0bxd7eXm7fvm0wbdKkSeLl5SWenp4yefJkvWlpaWni6ekpn3766UvXT7lHJZKDN5MREREVQoMHD8acOXPw+PHjDF/omV1paWkoX748unTpgi+++CJXlgkAgYGBCA4OxowZM3JtmURERES56eHDhyhSpAgmTJhg8CTBq1iyZAn69++P69evw8nJKVeWuW7dOvTo0QOXLl2Cp6dnriyTXo7vlCIiov+kp0+f6v0dHR2NJUuWoH79+rkWkAKevbPh888/x6xZs3L8CM2LtmzZggsXLmDUqFG5sjwiIiKiV/Vi3wp4/v6t4ODgXF3XW2+9heLFi2PWrFm5tszJkydjwIABDEiZGEdKERHRf1KVKlUQHByMcuXK4d69e5g3bx5u376NnTt3okGDBvldPCIiIqICZeHChVi4cCFatmwJe3t77Nu3D8uXL0ezZs2MvtScCOCLzomI6D+qZcuWWLVqFebOnQuVSoWqVati3rx5DEgRERER5UClSpVgbm6OKVOmID4+Xnn5+YQJE/K7aPQa40gpIiIiIiIiIiIyOb5TioiIiIiIiIiITI5BKSIiIiIiIiIiMjm+U+oFWq0Wt2/fhoODA1QqVX4Xh4iIiAoBEcGjR4/g5eUFM7PX654g+z5ERESU27La92FQ6gW3b9+Gj49PfheDiIiICqEbN27A29s7v4uhh30fIiIiyisv6/swKPUCBwcHAM82nKOjYz6XhoiIiAqD+Ph4+Pj4KP2M1wn7PkRERJTbstr3YVDqBbph646OjuyYERERUa56HR+PY9+HiIiI8srL+j6v10sNMjF79mxUqlRJ6TDVqVMHmzdvVqYnJiaif//+cHFxgb29PTp27Ih79+7lY4mJiIiIiIiIiCgjBSYo5e3tjf/97384evQojhw5gsaNG6Nt27b4559/AABDhgzBhg0bsHLlSuzZswe3b99Ghw4d8rnURERERERERERkjEpEJL8LkVPOzs6YOnUqOnXqhKJFi2LZsmXo1KkTACAyMhLlypXDwYMHUbt27SwvMz4+HhqNBnFxcRzCTkRERLnide5fvM5lIyIiooIpq/2LAjNSKr20tDSsWLECCQkJqFOnDo4ePYqUlBSEhIQoeQICAlC8eHEcPHgwH0tKRERERERERETGFKgXnZ8+fRp16tRBYmIi7O3tsXbtWpQvXx4nTpyApaUlnJyc9PK7u7vj7t27mS4zKSkJSUlJyt/x8fEAgNTUVKSmpgIAzMzMYGZmBq1WC61Wq+TVpaelpSH9gLOM0tVqNVQqlbLc9OnAs2BbVtLNzc0hInrpKpUKarXaoIwZpbNOrBPrxDqxTqwT62S6Or1O2PdhnVgn1ol1Yp1YJ9bpden7FKigVNmyZXHixAnExcVh1apVCAsLw549e15pmZMmTcL48eMN0o8fPw47OzsAQNGiReHv748rV67gwYMHSh5vb294e3vj/PnziIuLU9JLliwJNzc3nDlzBk+fPlXSAwIC4OTkhOPHj+vt4EqVKsHS0hJHjhzRK0P16tWRnJyMU6dOKWlqtRo1atRAXFwcIiMjlXQbGxtUrlwZUVFRuHz5spKu0WhQrlw53L59Gzdv3lTSWSfWiXVinVgn1ol1Ml2dihYtitcF+z6sE+vEOrFOrBPrxDq9Ln2fAv1OqZCQEPj7+6Nr165o0qQJYmNj9UZL+fr6YvDgwRgyZEiGyzB2t9DHxwfR0dHKc4+FNXLJOrFOrBPrxDqxTqyTaer0+PHj1+a9Tez7sE6sE+vEOrFOrBPr9Lr0fQp0UKpx48YoXrw4vvnmGxQtWhTLly9Hx44dAQDnzp1DQEAAX3RORERE+e517l+8zmUjIiKigimr/YsC8/jeqFGj0KJFCxQvXhyPHj3CsmXL8Mcff2Dr1q3QaDTo06cPhg4dCmdnZzg6OmLgwIGoU6dOtgJSRERERERERERkGgUmKHX//n306tULd+7cgUajQaVKlbB161Y0bdoUADBjxgyYmZmhY8eOSEpKQmhoKL7//vt8LjURERERERERERlToB/fywscwk5ERES57XXuX7zOZSMiIqKCKav9i9frG8VERERERERERPSfwKAUERERERERERGZHINSRERERERERERkcgxKERERERERERGRyTEoRUREREREREREJsegFBERERERERERmRyDUkREREREREREZHIMShERERERERERkckxKEVERERERERERCZnnt8FICIiIiKiwk2lOpbfRSAjRKrmdxGI6D+OI6WIiIiIiIiIiMjkGJQiIiIiIiIiIiKTY1CKiIiIiIiIiIhMjkEpIiIiIiIiIiIyOQaliIiIiIiIiIjI5BiUIiIiIiIiIiIik2NQioiIiIiIiIiITI5BKSIiIiIiIiIiMjkGpYiIiIiIiIiIyOQYlCIiIiIiIiIiIpNjUIqIiIiIiIiIiEyOQSkiIiIiIiqURo50x6FDZREfXxn37lXE2rUlUaaMlTLd19cSIlWN/uvUySnD5bq5mWPBAl/culUBCQlVsHmzP0qVstLLM316MURHV8L16xXQo0cRvWmdOjlh/Xr/XK0rEVFBxKAUEREREREVSg0b2mPWrAeoXfscmja9CAsLFbZtKwVb22c/g27cSIaHxym9f599dhuPHqVh8+b4DJe7bl1JlCxpibZtLyMw8F9cu5aMHTueL7dVKw169HBGs2YXMWLELfz0ky9cXNQAAEdHM0yc6IX+/a/n/QYgInrNmed3AYiIiIiIiPJCixaX9P4OD7+GBw8qoVo1W+zd+xhaLXDvXqpenvbtnfDrr7FISNAaXWbp0laoU8ceb7xxFmfPJgIA3n//Bu7erYju3Ytg3rxolCtnjT/+eISjR5/g6NEn+Pprb5QoYYXo6CeYMqUYZs+Owo0bKXlTaSKiAoQjpYiIiIiI6D9Bo3k2WikmJtXo9KpVbRAYaIt586IzXIaVlQoAkJj4PGglAiQlCerXtwcAnDz5BNWr28LJSY2qVW1gY2OGixeTUK+eHapWtcW3397PrSoRERVoDEoREREREVGhp1IBX3/tjX37HuOffxKN5unTxxVnzz7FwYMJGS4nMjIR164lYdKkYnByUsPCQoURI9zh42MJT08LAMC2bY+wdGksDh8ui4UL/RAWdhUJCVrMnl0c7713He+/XxSRkeWxb18ZlC9vnSf1JSIqCBiUIiIiIiKiQm/WLB9UqGCNbt2uGJ1uba1Cjx5FMh0lBQCpqUCHDpdRpowVYmMr48mTKmjUyB6bNsVBqxUl3/jxd1C69FlUqvQv1q2Lw6hR7tixIx4pKcCnn3qgfv3z+OmnKCxe7Jeb1SQiKlD4TikiIiIiIirUZs70RqtWGjRocB63bhl/l1OnTkVga2uGxYtjXrq8Y8eeIjAwEo6OZrC0NENUVCr++qssjhx5YjR/2bJWePttZwQGRiIiwgV//vkYUVGp+PXXh1iwwA/29mZ4/Nj4O6yIiAozjpQiIiIiIqJCa+ZMb7Rv74TGjS/g6tXkDPP16eOC9evjEBVl/H1TxsTHaxEVlYpSpaxQvbotfvvtodF8c+YUx9Cht5CQoIVarYKFxbP3Uun+q1arsl4hIqJChEEpIiIiIiIqlGbN8sHbbzujR4+rePQoDe7u5nB3N4e1tX4QyN/fCg0a2OOnn4w/uvfvv+XRrp1G+btTJyc0bGiPEiUs0aaNBtu3l8K6dQ+xffsjg3nfeccFDx6k4vff4wAA+/c/RuPGDqhVyxZDhrjhn3+eIi4uLRdrTURUcPDxPSIiIiIiKpQ++KAoAGDPnjJ66eHhV7Fo0fPH9CIiXHDzZgq2bYs3upyAAGvly30A4Olpga++8oa7uznu3EnB4sUx+OKLuwbzubmZ45NPPFC37nkl7fDhJ5g+/R42biyF+/dTERZ29VWqSERUoKlERF6e7b8jPj4eGo0GcXFxcHR0zO/iEBERUSHwOvcvXueyUeGhUh3L7yKQESJV87sIRFRIZbV/wcf3iIiIiIiIiIjI5BiUIiIiIiIiIiIik2NQioiIiIiIiIiITI5BKSIiIiIiIiIiMjkGpYiIiIiIiIiIyOQYlCIiIiIiIiIiIpNjUIqIiIiIiIiIiEyOQSkiIiIiIiIiIjI5BqWIiIiIiIiIiMjkGJQiIiIiIiIiIiKTY1CKiIiIiIiIiIhMjkEpIiIiIiIiIiIyOQaliIiIiIiIiIjI5BiUIiIiIiIiIiIik2NQioiIiIiIiIiITI5BKSIiIiIiIiIiMjkGpYiIiIiIiIiIyOQYlCIiIiIiIiIiIpNjUIqIiIiIiIiIiEyOQSkiIiIiIiIiIjI5BqWIiIiIiIiIiMjkGJQiIiIiIiIiIiKTY1CKiIiIiIiIiIhMjkEpIiIiIiIiIiIyOQaliIiIiIiIiIjI5BiUIiIiIiIiIiIik2NQioiIiIiIiIiITI5BKSIiIiIiIiIiMjkGpYiIiIiIiIiIyOQYlCIiIiIiIiIiIpMrMEGpSZMmoUaNGnBwcICbmxvatWuHc+fO6eVJTExE//794eLiAnt7e3Ts2BH37t3LpxITEREREREREVFGCkxQas+ePejfvz/++usvbN++HSkpKWjWrBkSEhKUPEOGDMGGDRuwcuVK7NmzB7dv30aHDh3ysdRERERERERERGSMeX4XIKu2bNmi9/fChQvh5uaGo0ePokGDBoiLi8O8efOwbNkyNG7cGACwYMEClCtXDn/99Rdq166dH8UmIiIiIiIiIiIjCsxIqRfFxcUBAJydnQEAR48eRUpKCkJCQpQ8AQEBKF68OA4ePJgvZSQiIiIiIiIiIuMKzEip9LRaLQYPHox69eqhQoUKAIC7d+/C0tISTk5Oennd3d1x9+7dDJeVlJSEpKQk5e/4+HgAQGpqKlJTUwEAZmZmMDMzg1arhVarVfLq0tPS0iAiL01Xq9VQqVTKctOnA0BaWlqW0s3NzSEieukqlQpqtdqgjBmls06sE+vEOrFOrBPrZLo6vU7Y92Gd8qNOZmYCc/Pn6xRRISVFBbVaoFY/T9dqVUhNVcHcXGBm9jw9LU2FtDQVLCwEKtXz9NRUFbTajNMtLZ9vFwBISVFBBLC0FL305GQVVCrAwuLFdLMMy14Y6qTb54X52GOdWCfW6fXu+xTIoFT//v1x5swZ7Nu375WXNWnSJIwfP94g/fjx47CzswMAFC1aFP7+/rhy5QoePHig5PH29oa3tzfOnz+vjNwCgJIlS8LNzQ1nzpzB06dPlfSAgAA4OTnh+PHjeju4UqVKsLS0xJEjR/TKUL16dSQnJ+PUqVNKmlqtRo0aNRAXF4fIyEgl3cbGBpUrV0ZUVBQuX76spGs0GpQrVw63b9/GzZs3lXTWiXVinVgn1ol1Yp1MV6eiRYvidcG+D+uUH3WqVCkJb775SEm/fNkSy5drUK/eEwQFPVHST5ywxsaNDggNfYwqVRKV9L17bfHnn3bo1CkeJUsmK+kbNzrgxAlrRETEwtX1edmXL9fg8mVLDBoUoxesmTOnCOLjzTB8eLRenaZOdYGjoxbvvhurpCUnqzB1qiv8/FLQvfvz7RgVpcacOc6Fok66fVuYjz3WiXVinV7vvo9K0ofWCoABAwbgt99+w59//okSJUoo6bt27UKTJk0QGxurN1rK19cXgwcPxpAhQ4wuz9jdQh8fH0RHR8PR0RFA4Y1csk6sE+vEOrFOrBPrZJo6PX78GBqNBnFxcUr/Ir+w78M65Ued1OqjBX5U0YtlLwwjpRISqgAo3Mce68Q6sU6vd9+nwASlRAQDBw7E2rVr8ccff6B06dJ60+Pi4lC0aFEsX74cHTt2BACcO3cOAQEBOHjwYJZfdB4fH//adBqJiIiocHid+xevc9mo8FCpjuV3EcgIkar5XQQiKqSy2r8oMI/v9e/fH8uWLcNvv/0GBwcH5T1RGo0GNjY20Gg06NOnD4YOHQpnZ2c4Ojpi4MCBqFOnDr+8R0RERERERET0mikwQanZs2cDAIKDg/XSFyxYgPDwcADAjBkzYGZmho4dOyIpKQmhoaH4/vvvTVxSIiIiIiIiIiJ6mQITlMrKU4bW1taYNWsWZs2aZYISERERERERERFRTr1e3ygmIiIiIiIiIqL/BAaliIiIiIiIiIjI5BiUIiIiIiIiIiIik2NQioiIiIiIiIiITI5BKSIiIiIiIiIiMjkGpYiIiIiIiIiIyOQYlCIiIiIiIiIiIpNjUIqIiIiIiIiIiEyOQSkiIiIiIiIiIjI5BqWIiIiIiIiIiMjkGJQiIiIiIiIiIiKTY1CKiIiIiIiIiIhMjkEpIiIiIiIiIiIyOQaliIiIiIiIiIjI5BiUIiIiIiIiIiIik2NQioiIiIiIiIiITI5BKSIiIiIiIiIiMjkGpYiIiIiIiIiIyOQYlCIiIiIiIiIiIpNjUIqIiIiIiIiIiEyOQSkiIiIiIiIiIjI5BqWIiIiIiIiIiMjkGJQiIiIiIiIiIiKTY1CKiIiIiIiIiIhMjkEpIiIiIiIiIiIyOQaliIiIiIiIiIjI5BiUIiIiIiIiIiIik2NQioiIiIiIiIiITI5BKSIiIiIiIiIiMjkGpYiIiIiIiIiIyOQYlCIiIiIiIiIiIpNjUIqIiIiIiIiIiEyOQSkiIiIiIiIiIjI5BqWIiIiIiIiIiMjkzPO7AERERERUuKlU0/K7CJQBkY/yuwhERPQfxpFSRERERERERERkcgxKERERERERERGRyTEoRUREREREREREJsegFBERERERERERmRyDUkREREREREREZHIMShERERERERERkckxKEVERERERERERCbHoBQREREREREREZkcg1JERERERERERGRyDEoREREREREREZHJMShFREREREREREQmx6AUERERERVaQUHeWL++PW7deg8iH6Ft21IZ5p09OwQiH2HQoKqZLnPs2LoQ+Ujv37//9tbLM316MKKj++P69X7o0aOc3rROncpg/fr2Oa8UERFRIWGe3wUgIiIiIsordnYWOHnyPubPP421a9tlmK9du1KoXdsLt249ytJyz5yJQkjIr8rfqami/H+rViXRo0c5NGu2CqVLF8H8+aHYuvUqoqOfwtHREhMn1kdIyMoc14mIiKiwYFCKiIiIiAqtLVuuYMuWK5nm8fKyx8yZTRAaugobN3bI0nJTU7W4d++J0Wnlyrngjz9u4OjRezh69B6+/roRSpTQIDr6KaZMaYjZs0/ixo2sBb+IiIgKMz6+R0RERET/WSoVsGRJS0ydehhnz0Zneb7SpYvg1q33cOnSO1i6tCV8fByUaSdPPkD16u5wcrJC1arusLExx8WLsahXrxiqVnXHt98ey4uqEBERFTgcKUVERERE/1kff1wTqanabAWK/v77DsLDN+PcuRh4etpj7Ng62Lu3OypUWIDHj1OwbdtVLF36Lw4ffhtPn6YiLGwzEhJSMHt2CMLDt+D996tg4MBAREU9Rb9+27IVDCMqiBp/cD2/i0BG7Pq+eH4XgYhBKSIiIiL6b6pa1R2DBlVD1aqLszVf+scBT5+Owt9/38G1a/3QpUtZzJ9/BgAwfvwBjB9/QMn32Wd1sGPHNaSkpOHTT2ujYsWFaNXKH4sXt0D16ktzp0JEREQFDB/fIyIiIqL/pKCgYnBzs8X16+8iJWUoUlKGws9Pg+nTg3HlSt8sLycuLgnnz8eiVKkiRqeXLeuMt98ujzFj9iM42Ad//nkTUVFP8euv51Ctmgfs7S1yq0pEREQFCkdKEREREdF/0pIlZ7Fjh/5jRVu3dsSSJWexYMGZLC/Hzs4C/v4aLFny2Oj0OXOaYujQ3UhISIFabQYLi2f3hXX/Vat5n5iIiP6bGJQiIiIiokLLzs4CpUo5KX+XKKFB5cpFEROTiBs3HiEmJlEvf0qKFnfvJuD8+VglbceOzli79iJmzToOAJg6tSE2bLiEa9fi4eVlj/Hj6yItTbB8eaTB+t95pyIePHiK33+/DADYv/8Wxo2ri1q1PNGiRQn8808U4uKS8qDmRERErz8GpYiIiIio0Kpe3QN//NFV+XvGjEYAgIULz6B37y1ZWoa/vxNcXW2Uv729HbB8eSu4uFjjwYOn2LfvFmrX/hlRUU/15nNzs8Unn9RG3brLlLTDh+9i+vQj2LixA+7ff4KwsM2vUj0iIqICTSUikt+FeJ3Ex8dDo9EgLi4Ojo6O+V0cIiIiKgRe5/6FKcqmUk3Lk+XSqxP5yCTrUamy/nVDMh2RqiZZD7++93ri1/coL2W1f8EH2ImIiIiIiIiIyOQYlCIiIiIiIiIiIpNjUIqIiIiIiIiIiEyOQSkiIiIiIiIiIjI5BqWIiIiIiIiIiMjkzPO7AERERERERER54eHtv3H9xBw8enAayU/uo0LzuShaIhQAoE1LwZVD0xB9fTeexl+HuaUDinjXh3/tkbCyc8/S8q8d+x6X/54M74oRKF1/rJJ+Yf/nuHtuFdTmtihZ+2N4lGmvTLt/aSPunluNSi3n525liQqgAjVS6s8//0Tr1q3h5eUFlUqFdevW6U0XEXz22Wfw9PSEjY0NQkJCcOHChfwpLBEREREREeWrtJQnsHcphzJBXxhM06Y+xaOoM/Cr9iFqdNqICqFz8OThZZze3CdLy46/fxK3z/4MO5dyeulRV3fg/oX1qNxqKfzrjMK5Pz5G8tMYAEBqUjwu/z3VaHmI/osKVFAqISEBlStXxqxZs4xOnzJlCr799lv88MMP+Pvvv2FnZ4fQ0FAkJiaauKRERERERESU31x8G6FkreEoWrK5wTRzK0dUaf0z3Eq1gm0Rf2g8qqJM0Od49OA0Eh/dynS5qSkJOLtjEMoGT4aFlUZvWkLsRTgVqw1Ht0pwL90WaksHJD66AQC49NckFHvjbVg7FMu9ShIVYAUqKNWiRQtMmDAB7du3N5gmIvj666/x6aefom3btqhUqRIWL16M27dvG4yoIiIiIiIiInpRavIjACqYWzlmmu/Cn2Pg4tsYzt71DabZu5TDo/unkJIUh0cPTkObmggbjR8e3jmMRw/OwLti7zwqPVHBU2jeKXXlyhXcvXsXISEhSppGo0GtWrVw8OBBdOvWzeh8SUlJSEpKUv6Oj48HAKSmpiI1NRUAYGZmBjMzM2i1Wmi1WiWvLj0tLQ0i8tJ0tVoNlUqlLDd9OgCkpaVlKd3c3BwiopeuUqmgVqsNyphROuvEOrFOrBPrxDqxTqar0+skP/o+lpYqvTKkpAhEYJCenCxQqQALC8N0MzPA3Px5usiz5WSUrlYDavXzdK1WkJoKmJsDZmbP09PSBGlpz9apSrfa1FSBVptxemGpU2pqqknOFzMzgbn582NDRIWUFBXUaoFa/Txdq1UhNVUFc3OBmdnz9LQ0FdLSVLCwEKhUz9NTU1XQajNOt7R8fvwCQEqK6v/3k+ilJyer/n8/vZhulmHZC0OddPs8r9tqlUogooLaTIv0Z0KaVgWBCuZm+nVK1T7LZW4mWUw3gwoCdbp0AZCmNYNKJVCn245m////ZipR/h8AtAKkpCTj8l+T4FG6Dayt7QBooRUVtC+U/e6FDXgUdQbVOq7///RnyzI30yJNq4JL8YZ4XLYdjq5qDbW5NSqETIPa3Brn//wEFZpMxZ2zi3Hj9CJYWDujbMNJsHMu80p10qUbq5NWzGCm0iJdE6HUqaBeUwtjP6Ew1imrCk1Q6u7duwAAd3f9F9K5u7sr04yZNGkSxo8fb5B+/Phx2NnZAQCKFi0Kf39/XLlyBQ8ePFDyeHt7w9vbG+fPn0dcXJySXrJkSbi5ueHMmTN4+vSpkh4QEAAnJyccP35cbwdXqlQJlpaWOHLkiF4ZqlevjuTkZJw6dUpJU6vVqFGjBuLi4hAZGamk29jYoHLlyoiKisLly5eVdI1Gg3LlyuH27du4efOmks46sU6sE+vEOrFOrJPp6lS0aFG8LvKj7zNokLtesGbOnAeIj0/D8OEeemWYOvUuHB3VePfd59srOVkwdepd+PlZoXt3ZyU9KioVc+Y8QKVKtnjzzeePzly+nITly2NQr54DgoLslfQTJ55g48Y4hIZqUKWKrZK+d+9j/PnnI3TqVAQlS1op6Rs3xuHEiSeIiHCFq+vzLvPy5TG4fDmp0NTpyJEjJjlfKlVKwptvPkpXJ0ssX65BvXpPEBT0JF2drLFxowNCQx+jSpXnr+DYu9cWf/5ph06d4lGyZHK6OjngxAlrRETEwtX1edmXL9fg8mVLDBoUoxesmTOnCOLjzTB8eLRenaZOdYGjoxbvvhurpCUnqzB1qiv8/FLQvfvz4z0qSo05c5wLRZ10+zav22ofZ3tcj3ZEg7K3YG/9vK5/XfTEg0e2aFrxml5g6o9/ffA02RwtKl/Rq9PmkyVgY5mK4HI3lLRUrRk2nywBV4enqF3qjpL+ONESu//1gY/zI1Qu/qyM2wGUdn+IGAClPWJRxuP5trly3wbLfhwDa4sUfDjgHVjbPFv3+btFcO6OM2qUvIeiDk8QG3MfMxaPReNuP+KxuTUalL2BK/aJ8CoahxaVryh1eq9Pe5ibtX2+n+Z/Bxefeggqdw9ztn6DkWPn4eypg9i4aSgavb02x3UCgAePbPHXRU+DOl2PdsDJ626o6BOF4i7Pj1VdnQrqNbUw9hMKY52y2vdRSfrQWgGiUqmwdu1atGvXDgBw4MAB1KtXD7dv34anp6eSr0uXLlCpVPjll1+MLsfY3UIfHx9ER0fD0fHZkM3CGrlknVgn1ol1Yp1YJ9bJNHV6/PgxNBoN4uLilP5FfsmPvo+V1XS9MhTUUUXp0wvLSKmEhEEmOV/U6qMFflTRi2UvDCOlEhKqAMj7tjp00K3XYqTU9lklUKnFHLj4NdcbVaRNS8GprQPwJP4GqrX9GVY2RZTlvDhS6v7lbTi5+V2oVOrn65I0ACqoVGYI7nceMDPXq1NC7CUc3/gOqnfeiPuRv+DhnSOo1HwW0lKeYNfcNxDU58z/j8zKfp3Sp2d3pNT2mcUK5DW1MPYTCmOdstr3yfFIqeTkZFy5cgX+/v4wN8//AVceHs/uSt27d08vKHXv3j1UqVIlw/msrKxgZWVlkG5ubm5QL93Of5FuZ2Y1PaPtlZ10lUplND2jMmY3nXVinTJKZ51YJ4B1yqiM2U1nnf5bdcpNr9IPy4++T3Ky8XugxtJFjKdrtdlLT0t7Fpx50bO+umF6SorxMmaUXljqlH6f5+X5otWqkJysMkjXBWZelJqqAmCYnpKSvfTkZOPnorGyPNtPhukZlb0w1Cmr5/yrttUiz8qQpjVe9tQM0w3LnlG6QGU8XVRIlXTB3P//f11gRpuWgn+2D8TTh1dRpe0KqK1ckKo1WIxSdkev+qjRZZvetMjdH8G2iD+KV3kfMDPXq5OI4J/dn6BU3TEwt7BHmlaQpk1DqtYMKalp/59Ha3QbZLVO6eumNZpuBq2R5qAgX1MLYz+hMNYpK7IdTXry5AkGDhyIRYsWAQDOnz+PkiVLYuDAgShWrBhGjhyZo4K8qhIlSsDDwwM7d+5UglDx8fH4+++/8f777+dLmYiMUamO5XcRKAMiVfO7CEREmXpd+2FERK+r1JQEPI27qvydGH8Dj6L+gYWVEyxt3fDPtvfx6MEZVGo5HyJpSHpyHwBgYeUEM7UlAOD4+u4oWiIU3hXDYW5pD3uXsnrrUFvYwsKqiEE6ANz5dwUsbZzh6vfs3ccaj+q4cuRrxN09hpjrf8C2SGmDr/cR/ZdkO5Q1atQonDx5En/88Qesra2V9JCQkAwfkcstjx8/xokTJ3DixAkAz15ufuLECVy/fh0qlQqDBw/GhAkTsH79epw+fRq9evWCl5eX8ogfERERUUGWn/0wIqKC6NH9UziysiWOrGwJALh44AscWdkSVw5/haSEu4i6uh1JCXdweGULHFhUQ/kXd/eosozE+OtISYzNaBUZSn7yANeOfYfS9Z+/x8/RvQp8KvfFqU29cf/S7yjXaNqrV5KoAMv2SKl169bhl19+Qe3ataFK95D6G2+8gUuXLuVq4V505MgRNGrUSPl76NChAICwsDAsXLgQI0aMQEJCAvr164eHDx+ifv362LJli16njYiIiKigys9+GBFRQVSkWB00ev9ahtMzm6ZT5+39mU4PbGv8poClbVGj85aoPgglqg966XqJ/guyHZR68OAB3NzcDNITEhL0Okd5ITg4WO9FXi9SqVT4/PPP8fnnn+dpOYiIiIjyQ372w4iIiIhyW7Yf36tevTo2btyo/K3rAP3000+oU6dO7pWMiIiIiPSwH0ZERESFSbZHSn355Zdo0aIFzp49i9TUVHzzzTc4e/YsDhw4gD179uRFGYmIiIgI7IcRERFR4ZLtkVL169fHiRMnkJqaiooVK2Lbtm1wc3PDwYMHUa1atbwoIxERERGB/TAiIiIqXLI9UgoA/P398eOPP+Z2WYiIiIjoJdgPIyIiosIi20Gp+Ph4o+kqlQpWVlawtLR85UIRERERkSH2w4iIiKgwyXZQysnJKdOvu3h7eyM8PBxjx46FmVm2nw4kIiIiogywH0ZERESFSbaDUgsXLsQnn3yC8PBw1KxZEwBw6NAhLFq0CJ9++ikePHiAadOmwcrKCqNHj871AhMRERH9V7EfRkRERIVJtoNSixYtwvTp09GlSxclrXXr1qhYsSLmzJmDnTt3onjx4pg4cSI7Q0RERES5iP0wIiIiKkyyPa77wIEDCAwMNEgPDAzEwYMHATz7Msz169dfvXRElOfs7c0wY4Y3rl59A0+eVMH+/WVQvbptpvNYWqowYYIXrl59A4mJVXDlyhvo3dtFmR4S4oBz58ojLq4yFi/2hYXF80dNHB3NcO5ceRQvzveeEBFlF/thREREVJhkOyjl4+ODefPmGaTPmzcPPj4+AIDo6GgUKVLk1UtHRHnup5980bSpA3r2vIaKFf/Ftm2PsGNHaXh5WWQ4z6+/lkCTJg7o0+c6ypY9i+7dr+LcuUQAgEoFLFvmhx9+iEKdOudQvbod+vVzVeb93/+K4YcfonD9enKe142IqLBhP4yIiIgKk2w/vjdt2jR07twZmzdvRo0aNQAAR44cQWRkJFatWgUAOHz4MLp27Zq7JSWiXGdtrULHjk5o2/YS9u59DAAYP/4OWrfW4P33XTFmzB2DeUJDHdGwoT1KlvwHsbFpAIBr154HmFxdzVG0qAW+//4BkpIE69c/RLly1gCAOnXsUKOGLQYMuGGC2hERFT7shxEREVFhku2gVJs2bRAZGYk5c+bg/PnzAIAWLVpg3bp18PPzAwC8//77uVpIIsob5uYqmJurkJgoeulPn2pRv7690XnatNHgyJEnGDHCHT17OiMhQYv16+MwZsxtJCYKHjxIxe3byWjWzBE7dsQjKMgeixbFwNwcmD3bBxER16DVmqJ2RESFD/thREREVJhkOygFACVKlMD//ve/3C4LEZnY48daHDjwGGPGeODffxNx714Kund3Rp06drh4McnoPCVLWqJ+fXskJgrat78MV1dzfP+9D1xczBERcQ0A0KXLFcyY4Y1vvvHGpk3xmD8/CiNHemD37sdITBTs21cGrq7mmDnzAWbNemDKKhMRFXjshxEREVFhkaOg1MOHD3Ho0CHcv38f2heGPPTq1StXCkZEptGz51XMn++L27crIjVVcOzYEyxfHotq1Yy/7NzMTAUR4K23riA+/tn5P3ToLaxaVQIffHAdiYmC/fsTULPmOWWe0qWt0KuXMwIDI/Hnn2XwzTf3sXlzPM6cKYc//3yM06efmqSuRESFAfthREREVFhkOyi1YcMGvPXWW3j8+DEcHR2hUj3/qpZKpWJniKiAuXw5GcHBF2BrawZHRzPcvZuKFStK4PJl4yOl7txJwa1byUpACgD+/TcRZmYqeHtbGh1hNWdOcQwbdgtmZkDVqrZYuTIWT58K9ux5jIYN7RmUIiLKIvbDiIiIqDDJ9tf3hg0bhoiICDx+/BgPHz5EbGys8i8mJiYvykhEJvDkiRZ376bCyUmN0FAH/PbbQ6P59u9/DC8vS9jZPW8+ypSxQlqa4OZNwy/qRUS4ICYmFRs2xEGtfvbjycLi+X/V6tyvCxFRYcV+GBERERUm2Q5K3bp1Cx9++CFsbY0/2kNEBUuzZg4IDXWEn58lQkIcsHt3aURGJmHBgmgAwJdfemHRIl8l/7JlsYiOTsWCBb4oV84aQUH2mDq1GObPjzZ4YXrRoub49FMPDBx4EwDw8GEazp59isGD3VC7th2aNHHA/v0JpqssEVEBx34YERERFSbZDkqFhobiyJEjeVEWIsoHGo0as2b5IDKyPBYv9sO+fY8RGnoBqanPpnt6WqB4cUslf0KCFk2bXoCTkxpHjgTg55/9sGFDHD788IbBsr/5xhvTp9/HnTspSlp4+DV06+aM33/3x9Sp93DkyJM8ryMRUWHBfhgREREVJtl+p9Sbb76J4cOH4+zZs6hYsSIsLCz0prdp0ybXCkdEeW/lyodYufJhhtN7975mkHbuXBKaNbv40mX36HHVIO3w4ScoX/5sdopIRET/j/0wIiIiKkyyHZTq27cvAODzzz83mKZSqZCWlvbqpSIiIiIiA+yHERERUWGS7aDUi58eJiIiIiLTYD+MiIiICpNsv1OKiIiIiIiIiIjoVWV7pBQAJCQkYM+ePbh+/TqSk/U/Af/hhx/mSsGIiIiIyBD7YURERFRYZDsodfz4cbRs2RJPnjxBQkICnJ2dERUVBVtbW7i5ubEzRERERJRH2A8jIiKiwiTbj+8NGTIErVu3RmxsLGxsbPDXX3/h2rVrqFatGqZNm5YXZSQiIiIisB9GREREhUu2g1InTpzAsGHDYGZmBrVajaSkJPj4+GDKlCkYPXp0XpSRiIiIiMB+GBERERUu2Q5KWVhYwMzs2Wxubm64fv06AECj0eDGjRu5WzoiIiIiUrAfRkRERIVJtt8pFRgYiMOHD6N06dJo2LAhPvvsM0RFRWHJkiWoUKFCXpSRiIiIiMB+GBERERUu2R4p9eWXX8LT0xMAMHHiRBQpUgTvv/8+Hjx4gLlz5+Z6AYmIiIjoGfbDiIiIqDDJ9kip6tWrK//v5uaGLVu25GqBiIiIiMg49sOIiIioMMn2SCkiIiIiIiIiIqJXle2g1L1799CzZ094eXnB3NwcarVa7x8RERER5Q32w4iIiKgwyfbje+Hh4bh+/TrGjBkDT09PqFSqvCgXEREREb2A/TAiIiIqTLIdlNq3bx/27t2LKlWq5EFxiIiIiCgj7If9H3v3HVdl/f5x/H3YS8ABLhABTdw798gRWpmWI/NbjkytbDhTW6alZsMyM8s0rUwr00yz3GZZWmq490RRHKjgRjif3x/8OHkCFBQOgq/n48Gjzuf+3Pe5rnPuA5fXuQcAAMhPsnz6XnBwsIwxORELAAAAroM6DAAA5CdZbkp98MEHGjp0qA4ePJgD4QAAACAj1GEAACA/ydTpewULFrS7ZsGFCxcUHh4uLy8vubq62s09ffp09kYIAABwB6MOAwAA+VWmmlIffPBBDocBAACA9FCHAQCA/CpTTalu3brldBwAAABIB3UYAADIrzJ9TamjR49q0KBBSkhISLMsPj5egwcP1vHjx7M1OAAAAFCHAQCA/CnTTalx48YpISFBvr6+aZb5+fnp3LlzGjduXLYGBwAAAOowAACQP2W6KbVo0SJ17do1w+Vdu3bVTz/9lC1BAQAA4F/UYQAAID/KdFPqwIEDKlWqVIbLg4KCuD0xAABADqAOAwAA+VGmm1Kenp7XLXYOHjwoT0/P7IgJAAAA16AOAwAA+VGmm1J16tTRV199leHyL7/8UnfffXe2BAUAAIB/UYcBAID8yCWzEwcNGqSWLVvKz89PgwcPVtGiRSVJx48f19tvv63p06dryZIlORYoAADAnYo6DAAA5EeZbkrdc889mjhxol544QW9//778vX1lcViUXx8vFxdXTVhwgQ1a9YsJ2MFAAC4I1GHAQCA/CjTTSlJ6tOnjx544AF999132rt3r4wxuuuuu9ShQwcFBQXlVIwAAAB3POowAACQ32SpKSVJJUuWVP/+/XMiFgAAAFwHdRgAAMhPMn2hcwAAAAAAACC70JQCAAAAAACAw9GUAgAAAAAAgMPRlAIAAAAAAIDD3VRT6uzZs5oyZYqGDRum06dPS5L++ecfxcTEZGtwAAAAsEcdBgAA8oss331v8+bNatGihfz8/HTw4EH16tVLhQoV0ty5cxUdHa0vv/wyJ+IEAAC441GHAQCA/CTLR0oNGDBA3bt31549e+Th4WEbv++++/Tbb79la3AAAAD4F3UYAADIT7LclFq3bp369OmTZrxkyZKKjY3NlqAAAACQFnUYAADIT7LclHJ3d1dCQkKa8d27dysgICBbggIAAEBa1GEAACA/yXJT6sEHH9TIkSN19epVSZLFYlF0dLSGDBmi9u3bZ3uAAAAASEEdBgAA8pMsN6Xee+89nT9/XoGBgbp06ZKaNGmiMmXKqECBAho1alROxAgAAABRhwEAgPwly3ff8/Pz09KlS7V69Wpt3rxZ58+fV40aNdSiRYuciA8AAAD/jzoMAADkJ1luSqVq2LChGjZsmJ2xAAAAIBOowwAAQH6Q5abUhx9+mO64xWKRh4eHypQpo8aNG8vZ2fmWg7tZEydO1DvvvKPY2FhVrVpVEyZM0N13351r8QAAAGSHvFCHAQAAZFaWm1Lvv/++Tp48qYsXL6pgwYKSpDNnzsjLy0s+Pj46ceKEwsLCtHLlSgUHB2d7wDfy7bffasCAAfrkk09Up04dffDBB4qMjNSuXbsUGBjo8HgAAACyy+1ehwEAAGRFli90Pnr0aNWuXVt79uxRXFyc4uLitHv3btWpU0fjx49XdHS0ihUrpv79++dEvDc0btw49erVSz169FCFChX0ySefyMvLS59//nmuxAMAAJBdbvc6DAAAICssxhiTlRXCw8M1Z84cVatWzW48KipK7du31/79+/Xnn3+qffv2OnbsWHbGekOJiYny8vLS999/r3bt2tnGu3XrprNnz+rHH39Ms86VK1d05coV2+OEhAQFBwerePHicnLKcs8OuKGYmKu5HQIyULKka26HACCfslqtOnbsmOLj4+Xr63vT28mOOiw3ap+YmPM5sl3cupIlfRzyPNQ/tydH1T6nziY75HmQNUX8OdUbOSeztU+WT987duyYkpKS0ownJSUpNjZWklSiRAmdO3cuq5u+ZadOnVJycrKKFi1qN160aFHt3Lkz3XXGjBmjESNGpBl3dEMNQO6LicntCADg+rKjDqP2wbViYuJzOwTkImqfO1vMhdyOALiJptQ999yjPn36aMqUKapevbqklG/nnn76aTVr1kyStGXLFoWGhmZvpDlk2LBhGjBggO0x3xbeuRz1TSHubHxTePty1LeF565aHfI8yJoCrjl7dHTqt4W3KjvqsNyofQAAdy5qn9tXTtY/ma19styUmjp1qh5//HHVrFlTrq4ph3smJSWpefPmmjp1qiTJx8dH7733XlY3fcuKFCkiZ2dnHT9+3G78+PHjKlasWLrruLu7y93dPc34zp07b+nw+uuxWN7Nke3i1hw5Mii3Q8AdoNkz0bkdAjKw4uNSDnmet6JOOeR5kDVDqxfJ0e0nJCTIz8/vlreTHXVYbtQ+AIA7F7XP7Ssn65/M1j5ZbkoVK1ZMS5cu1c6dO7V7925JUrly5VSuXDnbnHvuuSerm80Wbm5uqlmzppYvX267ppTVatXy5cv17LPP5kpMAAAA2eV2rsMAAACyKstNqVQRERGKiIjIzliyxYABA9StWzfVqlVLd999tz744ANduHBBPXr0yO3QAAAAssXtWocBAABkxU01pY4cOaL58+crOjpaiYmJdsvGjRuXLYHdrEceeUQnT57Ua6+9ptjYWFWrVk2LFi1Kc/Fz2Bs+vL46dy6n4GBfJSYma8OG43r55d/199+x113vmWeqafDg2ipWzFubNp3Uc88t17p1/67z3ntN1b17RV24cFVDh/6umTN32JZ16HCXunatqAcf/CHH8gIAIL+5neswAACArMhyU2r58uV68MEHFRYWpp07d6pSpUo6ePCgjDGqUaNGTsSYZc8++yyn62XR7t2n9eyzy7V/f7w8PV3Uv39NLVnSUWXKTNGpU5fSXadTp3IaN66pnnpqmf7665j69auhxYs7qFy5z3Xy5EU98ECYunQpr3vv/V5lyxbU559HavHig4qLuyRfXzeNGtVQLVrMdnCmAADkXXmhDgMAAMisLF9qfdiwYRo0aJC2bNkiDw8PzZkzR4cPH1aTJk3UsWPHnIgRDjBr1k4tXx6tAwfitX17nAYM+FV+fu6qUiUgw3UGDKilzz7bounTt2rHjjg99dRSXbx4VU88UUmSVL58Yf3662Ft2HBc33yzUwkJiQoNTbnQ2dtvN9GkSZt0+HDGt6wG4BgH1r2vv2Y106rPIvT71MraOL+L4o9HXXedmK1f6e9vI/XblIr6bUpFbZjbTnGHVtrN2fPHSP3+eRX9+WVdxe62PyLyxL6F2vzzE9meC5DfUYcBAID8JMtNqR07dqhr166SJBcXF126dEk+Pj4aOXKkxo4dm+0BwvFcXZ3Uu3cVnT17WZs2ncxwTs2aRbVs2SHbmDHSsmXRqlevhCRp06aTqlWrqPz93VWjRlF5erpo794zatCgpGrUKKoPP/zHIfkAuD4vv1CVbTRSdz+yRDUemiOPAkHa9NPjSrwUl+E67j7FFV53iGp1+Em1OixQwZL1tWVRL104nXLh5VMHl+nEnvmq+sAMhdcbpl2/DlHipdOSpKQrCdr/1zu6q9EbDskPyE+owwAAQH6S5aaUt7e37foFxYsX1759+2zLTp3iVo952f33h+ncued1+XJ/9e9fUy1bfq+4uPRP3StSxFMuLk46fvyC3fjx4xdUrJi3JGnJkoOaMWOH1q17TNOnt1K3br/owoWrmjSphZ56aqmefrqadu58QqtXP6oKFQrneH4A0lf0rnYqFNRQnr6l5F3oLpVp8KqSE8/pfNyODNcpUrqFCoc0k5d/qLz8wxRW50U5u3op/nhKs/nCmb3yL1lXvoFVVLRsWzm7FdDlc4clSfvWjlHJio/Jo0BJh+QH5CfUYQAAID/J8jWl6tatq9WrV6t8+fK67777NHDgQG3ZskVz585V3bp1cyJGZLMuXcrr009b2h63bj1Hq1fHaOXKw6pW7UsVKeKpXr2q6Lvv2qhOna918uTFm36uESP+1IgRf9oev/ZaPS1bdkhXrybrlVfqqnLl6XrggXB9+WVr1ao145byAnDrrMmJOrp9plzcfOVTuEKm1jHWZJ3Yt1DJVy/Jr2jKNW18CpfXse0zdfVKvC4nRMuadFmefqV19tg6nTu5VXc1ejMn0wDyLeowAACQn2S5KTVu3DidP39ekjRixAidP39e3377rcqWLcsdX/KI+fP36q+/jtkex8SkvJ8XL17Vvn1ntW/fWf311zHt3t1TPXtW0ltv/Z1mG6dOXVJSklVFi3rbjRct6q3Y2Atp5ktSuXKF9NhjFVS9+pd64olK+u23Izp16pK++26Xpk1rJR8fV50/fzUbMwWQWacOLtf2pc8qOemS3LwDVbXNDLl5FrruOufjduqfuQ/JmnxFzq7eqtzqU3kXukuSVLhUEyXc9ZA2fN9GTi4eKt/sPTm7eGr3by+rfLP3FLPtKx3Z8oVcPQsqoslbtvUAXB91GAAAyE+y3JQKCwuz/b+3t7c++eSTbA0IOe/8+as6f/7sDec5OVnk7p7+LnL1qlUbNhxX8+al9OOPeyVJFovUvHkpffRR+hdI/vTTlhowYKUuXLgqZ2cnubqmnD2a+l9n5yyfTQogi2J3/6Ddq16yPa5y/xfyL3G3Cpasp1qdftHVS6d1bMcsbVvyjGo+/KPcvIpkuC0v/zDV6vSLkhPP6cS+n7VjxUBVb/utrcEUWru/Qmv3t80/sO4DFQxqKIuTiw5t+Ei1H1msuEPLtX15f9XuuDDnkgbyEeowAACQn2S5CxAWFqa4uLQXvz179qxdoYS8w8vLVaNGNVSdOsVVqpSvatQoqqlTI1WypI9mz95lm7dsWUf17Vvd9njcuPXq1auKunatqIiIQpo0qaW8vV01bdrWNM/x5JOVdfLkJf30035J0h9/xKhZs1KqU6e4+vevqW3bTik+/krOJwvc4YqUbqlanX6x/RQIrCJJcnb1kpdfafkVq6GIe96RxclFx3Z+e91tOTm7ycuvtAoEVFZ43SHyKVxeR7ZMS3fuhTN7dXzPDwq9e6DOxqyVX4m75eZZWIHhD+j8qa1KSjyf7bkC+RF1GAAA2euHUYM0rEaAVn99/S96Dmz4U1+88D+NvreShtUI0LaVP6eZ89uXE/Vm8/J6s3l5/f7Vx3bLords0IQuzZWclJSt8ed1WT5S6uDBg0pOTk4zfuXKFcXExGRLUHCs5GSrIiIKqVu3iipSxFNxcZe1bl2sGjX6Rtu3/1v4hof7q0gRT9vj777bpYAAL40c2UDFinlp48aTatXqe504YX8NqsBAL738cl3Vrz/TNrZuXazee2+9Fi58WCdOXFS3br/kfKIA5OLmIxc3nxvOM8Yqa3Jilrad0TrGGO1a9ZLK1H9VLq7eMiZZxpryx9hqvfr/c9L+XQGQFnUYAADZZ9uKhTq8Zb18A4rdcG7i5YsqfldF1WrbRTMGdU+z/NjubVr2yVh1++BrGWP0Rb//qWzdpipWtoKSk5I0b/QgPfTKODm7ZLkNk69l+tWYP3++7f8XL14sPz8/2+Pk5GQtX75cpUuXztbg4BhXriSrffv5N5wXGvpZmrGJE6M0cWL6p+ulOnHiYrrrvvHGGr3xxprMBwog2yVfvaiDGz5SkdIt5O4dqKuXz+jI1i+UeOG4AsPvt82Lmv+oAkIjFVS5uyRp39qxKlyqqdx9Sij56gUd3/Ojzh5dq6oPfJXmOY7t+EZunoVUpHQLSZJfsVo6sP4Dxcf+o9PRv8qrYFm5uvulWQ/Av6jDAADIXvEnjmn+28P0xMTvNP35LjecX65BC5Vr0CLD5ScP7lGxMhUUfncjSVKxshVSxspW0O9ffqTQGvUUXLF6huvfqTLdlGrXrp0kyWKxqFu3bnbLXF1dVbp0ab333nvZGhwAIIdZnHTx7F5tXfK9rl46I1cPf/kGVlX1drPtLj5+OSFaVy+fsT2+eumUdqwYoCsXTsjFrYB8Ckeo6gNfqVBwI7vNJ148qUP/fKQaD821jfkWrabgqr20+ececvMsrPLNuDgzcCPUYQAAZB+r1arvXnlGjbv2VdHwiGzZZrEyFXQqep/OHjsiY4xOHdqnouHlFXf4gNbPn6Xnvl6eLc+T32S6KWW1WiVJoaGhWrdunYoUyfjitwCAvMHZxUOVW02+4bx6j/1h9zjinncytX03r4A060pSaK0XFFrrhcwFCYA6DACAbPTb9A/l5OKi+o/2zrZtBobdpchnX9bUZzpIklo994oCw+7SlKfaq/ULw7V7zQot//QdObm4qM2gUQqtWT/bnjsvy/LJjAcOHMiJOAAAAHAD1GEAAGRN1M/fa96ogbbH3T6cqT9mTdZzM1fIYrFk63PV6dBddTp0tz3esOAbuXv7qFSVWhr3UD31nbFE8cePadaw3nrxpw1ycXPP1ufPi27qClvLly/X8uXLdeLECds3d6k+//zzbAkMAAAAaVGHAQCQeRWatFJwpRq2x1uXzdeF06c09r5qtjFrcrJ+fn+4/pg5WUMW/pMtz3vhTJyWT35XfabM1+Gt/6hISLiKlEr5sSYl6dShfSpWtkK2PFdeluWm1IgRIzRy5EjVqlVLxYsXz/bOIgAAANJHHQYAQNa4e/vI3fvfu0/XfrirIhpH2s2Z1reTqt/fUTUfvPEFzzPrp/deVcP/9ZFf0RI6si1KyUlXbcuSk5NktXL3aekmmlKffPKJpk+frscffzwn4gEAAEAGqMMAALg13v6F5O1fyG7MycVVPoUDFVC6jG1sSp+HVeGe+1S/85OSpCsXzyvu8L+n0Z+JidbRXVvk5VtQ/sWD7La3Z+2vOhW9Tx1HfiRJCqpYXScP7tWuP5YpPvaonJydFRBSRriJplRiYqLq1+eCXLfCmEG5HQIAAMiDqMMAAHCMuCMHdfHsadvjmO2b9FnvdrbHC8e9Kkmq0eYRdRzxkW386uVLmj92qB596zM5OTlJkvyKltCDL47W968/LxdXd3UcMUGuHp6OSeQ2ZzHGmKysMGTIEPn4+OjVV1/NqZhyVUJCgvz8/BQfHy9fX9/cDgdAPtPsmejcDgEZWPFxKYc8z1tRpxzyPMiaodVz9m522VVf5EQdRu0DAMhJ1D63r5ysfzJbX2T5SKnLly9r8uTJWrZsmapUqSJXV1e75ePGjct6tAAAALgh6jAAAJCfZLkptXnzZlWrVk2StHXrVrtlXGwTAK7PUUfjAMifqMMAAEB+kuWm1MqVK3MiDgAAANwAdRgAAMhPnG52xb1792rx4sW6dOmSJCmLl6YCAADATaIOAwAA+UGWm1JxcXFq3ry57rrrLt133306duyYJKlnz54aOHBgtgcIAACAFNRhAAAgP8lyU6p///5ydXVVdHS0vLy8bOOPPPKIFi1alK3BAQAA4F/UYQAAID/J8jWllixZosWLFysoKMhuvGzZsjp06FC2BQYAAAB71GEAgLxmaPUiuR0CbmNZPlLqwoULdt/MpTp9+rTc3d2zJSgAAACkRR0GAADykyw3pRo1aqQvv/zS9thischqtertt9/WPffck63BAQAA4F/UYQAAID/J8ul7b7/9tpo3b67169crMTFRL774orZt26bTp0/rjz/+yIkYAQAAIOowAACQv2T5SKlKlSpp9+7datiwodq2basLFy7o4YcfVlRUlMLDw3MiRgAAAIg6DAAA5C9ZPlJKkvz8/PTyyy9ndywAAAC4AeowAACQX2T5SKlp06Zp9uzZacZnz56tL774IluCAgAAQFrUYQAAID/JclNqzJgxKlIk7S0dAwMDNXr06GwJCgAAAGlRhwEAgPwky02p6OhohYaGphkPCQlRdHR0tgQFAACAtKjDAABAfpLlplRgYKA2b96cZnzTpk0qXLhwtgQFAACAtKjDAABAfpLlptSjjz6q559/XitXrlRycrKSk5O1YsUKvfDCC+rcuXNOxAgAAABRhwEAgPwly3ffe+ONN3Tw4EE1b95cLi4pq1utVnXt2pVrGQAAAOQg6jAAAJCfZKkpZYxRbGyspk+frjfffFMbN26Up6enKleurJCQkJyKEQAA4I5HHQYAAPKbLDelypQpo23btqls2bIqW7ZsTsUFAACAa1CHAQCA/CZL15RycnJS2bJlFRcXl1PxAAAAIB3UYQAAIL/J8oXO33rrLQ0ePFhbt27NiXgAAACQAeowAACQn2T5Quddu3bVxYsXVbVqVbm5ucnT09Nu+enTp7MtOAAAAPyLOgwAAOQnWW5KffDBBzkQBgAAAG6EOgwAAOQnWW5KdevWLSfiAAAAwA1QhwEAgPwky9eUkqR9+/bplVde0aOPPqoTJ05Ikn755Rdt27YtW4MDAACAPeowAACQX2S5KbVq1SpVrlxZf/31l+bOnavz589LkjZt2qThw4dne4AAAABIQR0GAADykyw3pYYOHao333xTS5culZubm228WbNmWrt2bbYGBwAAgH9RhwEAgPwky02pLVu26KGHHkozHhgYqFOnTmVLUAAAAEiLOgwAAOQnWW5K+fv769ixY2nGo6KiVLJkyWwJCgAAAGlRhwEAgPwky02pzp07a8iQIYqNjZXFYpHVatUff/yhQYMGqWvXrjkRIwAAAEQdBgAA8pcsN6VGjx6tiIgIBQcH6/z586pQoYIaN26s+vXr65VXXsmJGAEAACDqMAAAkL9YjDHmZlY8fPiwtmzZovPnz6t69eoqW7ZsdseWKxISEuTn56f4+Hj5+vrmdjgAgHzmrSiu+3M7Glq9SI5uP7vri+ysw6h9AABAdstsfeGS2Q1arVa98847mj9/vhITE9W8eXMNHz5cnp6e2RIwAAAA0kcdBgAA8qNMn743atQovfTSS/Lx8VHJkiU1fvx49e3bNydjAwAAgKjDAABA/pTpptSXX36pjz/+WIsXL9a8efO0YMECff3117JarTkZHwAAwB2POgwAAORHmW5KRUdH67777rM9btGihSwWi44ePZojgQEAACAFdRgAAMiPMt2USkpKkoeHh92Yq6urrl69mu1BAQAA4F/UYQAAID/K9IXOjTHq3r273N3dbWOXL1/WU089JW9vb9vY3LlzszdCAACAOxx1GAAAyI8y3ZTq1q1bmrHHHnssW4MBAABAWtRhAAAgP8p0U2ratGk5GQc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",
      "text/plain": [
       "<Figure size 1200x1200 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Adjust the color and position of value labels based on the bar color and value size\n",
    "\n",
    "\n",
    "# Define custom intervals\n",
    "intervals = [(0, 39), (40, 59), (60, 74), (75, 100)]\n",
    "categories = [f\"{lower}-{upper}\" for lower, upper in intervals]  # Label intervals\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def create_bar_plot(ax, title, data, colors, ylabel='Percentage Change', place_neg_below=False):\n",
    "    ax.bar(categories, data, color=colors)\n",
    "    ax.set_title(title)\n",
    "    ax.set_ylabel(ylabel)\n",
    "    ax.set_xlabel('Information Quality')\n",
    "    ax.set_ylim(-30, 31)\n",
    "    ax.grid(axis='y', linestyle='--', alpha=0.7)\n",
    "    ax.axhline(0, color='black', linewidth=2)  # Bold y=0 line\n",
    "\n",
    "    # Add value labels with visibility adjustments\n",
    "    for j, (v, color) in enumerate(zip(data, colors)):\n",
    "        # Choose text color for visibility\n",
    "        text_color = 'white' if color in ['darkblue', 'mediumblue','darkorange'] else 'black'\n",
    "        \n",
    "        # Place negative values below the bar if specified\n",
    "        vertical_offset = -1.5 if place_neg_below and v < 1 else (1 if v < 0 else -3)\n",
    "        if abs(v) < 1 and not place_neg_below:\n",
    "            vertical_offset = 3 if v > 0 else -5  # Move small values away from bars if not placing negatives below\n",
    "\n",
    "        ax.text(j, v + vertical_offset, f\"{v:.1f}%\", ha='center', color=text_color, fontsize=10)\n",
    "        #vertical_offset = 1 if v < 0 else -3\n",
    "        #if abs(v) < 1:\n",
    "        #    vertical_offset = 3 if v > 0 else -2  # Move small values away from bars\n",
    "        \n",
    "# Colors for each interval in each dataset\n",
    "colors_decahose = ['darkblue', 'mediumblue', 'royalblue', 'skyblue']\n",
    "colors_panel = ['darkorange', 'orange', 'gold', 'lightcoral']\n",
    "\n",
    "# Create combined plot\n",
    "fig, axs = plt.subplots(2, 2, figsize=(12, 12), sharey=True)\n",
    "\n",
    "# Plot for Decahose dataset\n",
    "create_bar_plot(axs[0, 0], 'Decahose Dataset: Volume Change (%)', y_deca_vol, colors_decahose)\n",
    "create_bar_plot(axs[0, 1], 'Decahose Dataset: Market Share Change (%)', y_deca, colors_decahose)\n",
    "\n",
    "# Plot for Twitter Panel dataset\n",
    "create_bar_plot(axs[1, 0], 'Twitter Panel Dataset: Volume Change (%)', y_vol, colors_panel)\n",
    "create_bar_plot(axs[1, 1], 'Twitter Panel Dataset: Market Share Change (%)', y, colors_panel, place_neg_below=True)\n",
    "# Manually add label for the 0-39 Twitter Panel market share change value\n",
    "axs[1, 1].text(0, -0.5133828762590024 - 1.5, f\"{-0.5133828762590024:.1f}%\", ha='center', color='black', fontsize=10)\n",
    "\n",
    "# Adding a main title\n",
    "fig.suptitle('Changes in Content Volume and Market Share for Twitter Panel and Decahose Datasets', fontsize=16)\n",
    "\n",
    "# Display the combined plots\n",
    "plt.tight_layout(rect=[0, 0.03, 1, 0.95])\n",
    "plt.rcParams.update({'font.size': 12})\n",
    "\n",
    "#plt.savefig('marketshare_4bins_change.png', dpi=1200, bbox_inches='tight')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "db2a541d-89e8-45fa-a569-7e347eaa594d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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tXO1dgQIFbNeuXa76KWkLElOoUCHXfnv+/PlkjZNwHdxxxx1WtmxZy5Qpk7Vu3dratm1r2bJlcy37iRMnPMYNDAy08PBwq1y5srVv397atGljt912m0my9OnT26pVqzzGiYmJMUk2cOBACw0NtQIFCljnzp2tdevW9vzzz5tZ6u4vU6dOTbRdmzp1qqvelClTXMeOChUqWLdu3axGjRqu7eexxx7zaVlSwrl/XrkfOY/7P/zwg1v5wIEDXfGNGDHCbdiSJUtMktWvX9+t3FvbGBMT4zoulCtXzm37mzp1aoqODVu2bLG8efOaJMuZM6c1a9bMWrdu7Rq3fPnyHtuSc7m7d+9u0dHRliNHDuvQoYO1b98+2du/cz14a/Pj4uIsNDTUJNmLL75oZmZPPPGESbKCBQtaw4YNXX0wZ5+offv2Fh8f7zadhG1BTEyMBQcHW4MGDaxz586uY1VoaKitWbPGI4aUtglm5mrvUtquXktb6Es78OKLL7qmXbVqVevWrZurbRw5cqTX9vNqnOtl+vTpSdaLj4+36Ohok2RPP/202zBf25HFixdbpkyZTJJly5bN2rZta506dbIqVapYcHCwxcTEuNW/3us7pW1VXFycNWzY0CRZRESENW/e3Lp162aNGjVyreeNGze6jePL9poU574jyXbu3Jlk3c2bN7vqrl692m1YSvs99913n9WsWdPVb0jYbiXcXnxpDxYvXmzBwcGudrNjx47Wrl07q1q1qoWGhlrbtm09li0l52LJbXd9iQM3J5JPt5BevXqZJGvQoIFP4zs7PpKsT58+bh33v/76y3Lnzm2S7MMPP3Qb79SpU/bFF1+4nXSYmV24cMFGjx5tkqxFixYe83N2/iTZm2++6TZsyZIlroTCnj173IaNGDHCJFnJkiVt//79rvJz585Zx44dXdO88oT666+/NofDYVmyZLFly5a5Dfvpp58sT548Jsm+++47V/m4ceNMkg0aNMijwb1w4YItXrzYY7mS4oztSs4DWXBwsM2dO9dtmPPgHBkZaWfPnk3WfJwdbkn2119/pShGs8snlM6T8CeffNJt2detW2dRUVEmyaZMmeI2nq/bUHI6l1OmTDFJVrhwYdu8ebPbsGXLllnGjBktJCTE/vjjD7dhzngyZcrk0Rl2xlu0aFGP+V0tcXM1n3/+uatjd+W+YWbWqFEjk2Rjxoxxlb3xxhsmybJkyeLWCYqPj3fFmilTJjt8+HCyYr3W5JMku+uuu+zixYuuYV9++aVJsowZM1r+/Pk9to+JEye6fqcrde/e3SRZq1at7NChQ27DXnrpJZNkRYoUSVHyfM6cOXbs2DGv5UFBQZY5c2aP/cbX7XTevHmuhMLy5cvdhj311FOuaV5L8mnr1q0e7XhcXJzly5fP0qdPb6dOnUoy+TR//ny3dtHp+++/t4iICAsODra9e/e6DXO2MZKsYcOGdvLkSY/xvSWftmzZ4mq7HnnkEbf68fHxrs5u//797dSpU65hFy9edCWSr0wK+Hqi6eTcjqTLCayBAwfa22+/bT/++GOS21XCddC0aVO3dXDs2DErX768SbKnnnrKY9yZM2fa6dOnPZb/tddeM0lWqlQpj+OHM2EjXb4AExcX5zFdf+wvSbUJP/30kwUFBZnD4bAZM2a4DZs/f77rxOCbb75J8bKkRGLJJ2d/Yvz48W7lBQsWtFy5clnmzJmtTJkyyRonsfWQWJuYnHGdzp4960qCPvLII27t/5kzZ6xbt24mXU7ue5u3dDmRm5LkqZNzfG+xOdsvSfbtt9+amdnatWvt559/9qi7b98+VyJu1qxZbsMSnkDnz5/ffv/9d9ewS5cuWb9+/UySNWnSxG28690mXGtbmJJ2YPPmzRYYGGgBAQH2ySefuA17//33zeFw+DX5ZPZvn6Jnz55u5b60I3/99ZerDzhq1CiPPsyhQ4c8LsRdz/XtS1u1bNkyV6Iq4bbntG7dOjty5Ijr375ur0lJSfIpLi7OtRxvvfWW2zBf+j3OdX1l0jAhX9qD+vXrm+R5wczM7MSJEx6JM1/Oxcyu3u6mNA7cvEg+3UKaNWtmkqxr164+je/s+OTJk8fOnDnjMfyZZ54xyfsdL0nJlSuXBQQEeDT2zoakffv2XsdzLk/CA8vZs2ctQ4YMJskWLlzoMc7hw4ctPDzca+exWrVqJsnrnRBmZrNmzTJJ1qFDB1fZPffcY5Lc7oy5FldLPo0cOdLreMWLFzdJHie8iZk5c6ZrXr50YJ1XPypVquR1+PPPP+/qsCTk6zZ0tc5lXFyc6w609evXe63z3HPPmSSPK8TO9fDyyy97jHP+/HlXB+vKJN21Jp8uXrxoOXLkMEkendHdu3e7rvokvCvQecLiLdb4+HgrW7Zsik6krjX5lC9fPjt37pzHeM44qlat6nFSffHiRdcV2N27d7vKf/31V3M4HJYrVy6vHT8zsxYtWpgkjwSsr5wneV999ZVbua/bqbNz/9BDD3mdn7OjfC3JJzOzmjVrmsPhcHVOv/76a1eizMySTD4lxXki/tprr7mVOzulwcHBtn37dq/jXpl8WrJkiWXKlMmCg4O93nG4YMECky5f1UyYvHSKi4uz0qVLmyS3zu61Jp/MzMaPH2/p06d3rVfnX8aMGa137962detWj3Gc6yB9+vReT6CcbWpKL+447wbcsmWLW7kzYVO0aFGvySN/7S9JtQn9+/dP8pg8ePBgk2SNGzdO0bKkVGLJJ+dFlXr16rnKtm/f7jqh6tSpk0mygwcPuoYndreUP5NPzosIrVq18jr8n3/+sWzZsllQUJDbCaRz3tHR0V7v9EgOb8mnv//+2z788EPXnSTly5dPVoJw4cKFJsk6derkVp7wBPrLL7/0GO/AgQMmXb77KeHdozeyTbjS1drClLYDAwYMMEnWpUsXr/Nr27at35NPXbt2NUnWvHlzV5mv7cjw4cNNkrVu3TpF8SYmtde3L22Vs4+f2N3oV/J1e01KSpJPZubqQz777LPJmr5Z4v2e5CSfkpJYe+C848pbMswbX87FzK7e7qY0Dty8+Nrdf1DDhg29voTT+XLyxJ6/3rx5s5YsWaKdO3fqzJkzrmeDL126pPj4eP3555+qUKGCx3itW7f2Or0SJUro66+/dpvfhg0bdPr0aWXJkkVNmjTxGCdr1qxq3Lixx7O9R44c0dq1a5UuXbpE5+d87jnhc+xVq1bV66+/rlGjRsnM1KRJE79+kjqpdbF169Ykn31PTc73YMTExHgd3r9/f91///3atm2b9u/fr1y5crkN93UbSszGjRu1f/9+FSpUSJUqVfJax9vvl5C3dRsaGqrbbrtNGzdu1L59+5Q3b94UxZWUoKAgxcTE6Nlnn9W0adPUsWNH17Dp06crPj5edevWVeHChSVJe/fu1fbt2yV5X+8Oh0N9+/bViBEjtHTpUo0ZMybVYk1M/fr1FRYW5lFepEgR/fTTT2revLnHO8yCgoJUoEABHTt2TPv373d9TWr+/PkyMzVv3lwZM2b0Or969epp/vz5+v7779WqVatkx7l//3599dVX2rp1q06ePOl6P8KWLVskSb///rtatGjhMV5KttNLly5p5cqVkqSePXt6jaN3797atGlTsuNOTL9+/bRq1SpNnz5d48aNc72APLkvGj969Ki++uor/fLLLzp+/LguXrwoSdq2bZskJfoeogoVKui222676vTfffddDRw4UOnSpdNXX32lxo0be9T56quvJF3+nHRQkGdXIiAgQHXq1NEvv/yi77//XqVLl07WsiXHmDFjdM899+iLL77QsmXL9OOPP+qXX37RP//8oxkzZuiTTz7Rp59+6nWbqFy5stcv4V2t7frzzz/19ddf688//9Q///yjuLg4Sf++g+r3339XyZIlPca74447FBgY6FHuz/0lMc52P7H3C/Xv31+vvvqqVqxYobi4OI+4E1uW1FKzZk2lS5dOq1ev1tmzZxUeHu56l0zjxo115swZffLJJ1q8eLF69OihEydOaMOGDcqUKZMqV67st7iu5Nz2u3Tp4nV4hgwZVLlyZc2fP1/r1q3z6Ms0atRIkZGR1xSD891pV6pYsaJmz56tgIB/X+kaGxurb775RuvWrdPhw4cVGxsrM9M///wjKfH2IigoSM2aNfMoz5Ejh6KionT8+HEdPXpUOXLkkHRj2gRf28KUtgPOfSexY0NMTIzf3znj7HMnPCb72o58/fXXkqRBgwalKIbrvb5T0lZVrFhRgYGBmjZtmooWLep6d2hibuQxzMnbb+rka7/nalLaHlStWlW//vqrevTooTFjxuj222/3ur4k38/FkiMlceDmxq92C8maNask6fDhw9c0ncQ+PRwRESFJHi/CPXPmjHr16qU5c+YkOd1Tp05d8/z27t0rSUm+fNbbsJ07d8rMdO7cuat+svTvv/92/X+vXr20aNEiffDBB+rQoYMCAwNVsmRJ1apVSx07dlSDBg2SnFZKpXTdJ8a5LUiXt4eUJlWcB/rEPtmbKVMmRUdH69ixY9q7d69H8im1lsNpx44dkqTt27d7PQgnlPD382dMydGvXz89++yz+uabb7Rv3z7lzp1bZuZ6QWLCF40713nmzJldMV2pUKFCbnX9LbF15kzAJjbc2clNuE6dv+Hbb7/t9sJybxL7Db0ZN26cxo8f7+rkepMabc/Ro0dd/05sv0itT1x37txZw4YN07vvvqshQ4boiy++UJEiRbx+FOBKU6dO1YgRI3TmzJlE6yS2PpLzUu+9e/e6OvzffvutatWq5bWe8/d+9NFH9eijjyY5zZT83smVKVMmxcTEuBK5x48f15w5c/TII4/owIEDiomJ0e7duz2SjyltJ+Li4jR48GBNnjw50Q9kSClf5/7aX5JytXbf2f6cP39eR48e9Xipe3JfCu+r0NBQ1apVS4sWLdKKFSvUtGlTLV68WA6HQ40aNXJt887k07fffqv4+HjVr1/fLdnib87frlevXurVq1eSdb39dqmxHps2bepK+jg/ylK7dm3Xy3qd1qxZoy5duri+guhNYttuzpw5FRwc7HVYRESEjh8/7vUYcL3ahGtpC1PaDjj7pv4+NiTlyJEjkuT2sSFf25Hdu3dLUoq+znw917cvbVWhQoX00ksv6YEHHtDgwYM1ePBg5c+fX9WrV1erVq3UqVMnhYSEuKZxo49hcXFxro93XPkBqWvp9yTFl/bg6aef1k8//aQFCxZowYIFrg8l1atXTz169HD7qrqv52LJkZI4cHMj+XQLqVSpkt577z39+OOPXq9KJldKO2mjR4/WnDlzVLx4cT3zzDOqUqWKsmTJ4mrEa9SoodWrVyfaMfelU5hUAsLbMOfVgwwZMqhDhw7Jnk9AQIDef/99jRkzRl999ZVWrVqlVatW6Y033tAbb7yh1q1ba86cOal2tTe1OsgVKlRQQECA4uPjtW7dulS9oyc5Uruj7/z9cuTIoaZNmyZZN0uWLNclpuQoWrSoateurRUrVmjGjBkaPXq0li5dql27dikyMtLtbqgbIbEvlzhdbZ2lZJ0651W+fHmVK1cuybrVqlVL1jRnz56txx57TBkyZNCrr76qBg0auL7K53A4NGbMGD399NOp2vZcDxkyZFCnTp00ffp09evXT7Gxsa4v1SRlw4YNuvPOOxUYGKhnn31WrVu3Vr58+RQeHi6Hw6EpU6bozjvvTHR9pEuX7qrzyJYtm8qXL68FCxZo+PDhWrhwoTJnzuxRz/l716pVy3UikJhSpUpddb7XKioqSv369VOFChVUsWJFHTlyRKtWrfK4ayul28SkSZP05ptvKkeOHHrxxRdVo0YNZc+e3XXHYPfu3fXRRx+leJ37Y3/xt+RsP9eqUaNGWrRokRYtWqQmTZro22+/VZkyZZQ9e3ZJl09GnXdDOf/bqFEjv8eVkPO3a9asmSuuxOTPn9+jLDXW46hRo676pcqzZ8/qjjvu0KFDh9S3b1/dfffdKly4sCIiIhQYGKg//vhDxYoVS7X283q2CdfaFt6sx4bEmJk2btwoSSpTpoyr/Hq1I7fK+h4yZIg6d+6sL7/8UitXrtTKlSs1c+ZMzZw5U2PHjtWKFStcd0Pd6GPYL7/8ogsXLkhy/02vtd+TGF/bgxw5cmj9+vVatmyZFi9erFWrVumHH37QqlWr9NRTT+npp5/WQw89JMn3c7HkSEkcuLmRfLqFtGrVSiNHjtSJEyf05Zdfql27dtdlvrNmzZIkffzxxypbtqzHcOfttqkhd+7ckv79TLA33oY5ky8Oh0PTpk1L8YGuZMmSKlmypB544AGZmb799lt1795dc+fO1YwZM5J1Yng9RUVFqXbt2lq2bJneffddtW/fPkXj586dW1u3bnVd+bnSyZMnXZ+kdf4m/uT8/TJnzuzxOeubXf/+/bVixQpNnz5do0ePdj1C1bVrV7eTDOd6PHr0qE6dOuX17ifn75Hcde5MADtvl76S8+rm9eD8DWvWrKlXX301VabpbHvGjx/v9fGA1Gx7MmfOrNDQUMXGxmrXrl1eO5tJtUsp1a9fP02fPl1z585VYGBgoo/AJvTJJ5/IzDRkyBA9+OCDHsNTY32EhIToiy++UPfu3fXpp5+qbt26Wrx4sesuCyfn7922bVvdf//91zzf1FKhQgVlyZJFR44ccd0pcC2c2+DkyZPVpk0bj+G+rnN/7C9Xkzt3bm3fvl07duzw+giJs/0JCwvzuBJ/vTgTSYsXL9bGjRt19OhRt32jUaNGmjp1qrZu3XrDkk958+bV1q1b1b9//xt+gSEpy5cv16FDh1SxYkXXcSmh1Gw/pevbJlyPtjAh575zPY4N3syfP1/Hjx+XJLfHOH1tR/Lly6fff/9dW7dudb0aICk3an370lZlz55dAwcO1MCBAyVJW7duVb9+/bR69WqNGjVK7777rqQbfwx7//33JV3ueyR83YS/+j3X0h44HA7Vq1fPlfA+f/683nnnHd17770aM2aMOnbsqEKFCl3zudjVJDcO3NxurdT/f1yhQoXUrVs3SdJ9993nSg4k5vDhw4k+f50Szvl4u4K3cOHCVOngO1WqVEnh4eH6+++/XR3LhI4cOaJFixZ5lOfKlUtly5bVP//843qW3VcOh0MNGzZU9+7dJSlV3vHiDw8//LAk6csvv7zqI5Fm5nqfjfTvM9fOg/CVnAemIkWKpEryyZkkcT6zfiXn3XS//vqr63l2f7taTMnVqVMnRUREaNu2bZo3b55mz54tyf2RO0nKkyeP66DoLcGW8HG9xN7ncSXnb/Pbb795DDt79qyWLl2a3MW4Zs2bN5d0eXtMrUcck2p7Dh8+7LUt8FVQUJBq1qwpSfrggw+81nnvvfdSbX61atVS5cqVlTlzZrVv397j0VZvklof58+f12effZYqsQUHB2vmzJnq06ePtmzZotq1a3skMp2/t/OkJLmudb+72rxOnDjhemwgT548Ps0joaTW+ZYtW3w+Pvhjf7kaZ7ufWILf2e7Xrl37hr1Lo0KFCsqcObN++uknffjhh5LkdveaM9H09ttva9u2bcqbN6+KFi2a7OknZ/u7Wh3nb+c8SbxZObfdxB55cp78phZf2wRfXK+20Klu3bqSEj82zJgxI1Xnl9DJkyc1YsQISZf3hfLly7uG+dqOON/lNXXq1GTVv97rOzXbquLFi7vuiEnYXl/P7fVKP/74oytZOHLkSLenK3zt91yt3UrN9iAsLEx33XWXypYtq/j4eP3000+Sru1czJe+QWJx4OZG8ukW88orr6hw4cLauXOnatWq5ZZQcLpw4YKmTZumChUqeD0pTSnnc7SvvPKKW/nvv/+uu+6665qnn1B4eLgGDBggSRoxYoTrZa7S5ZfkDR48ONHnzZ988klJUt++fTV37lyP4WamH374Qd98842rbMaMGdqwYYNH3X/++cf1wkNvB4CbQePGjXXfffdJunyXzYsvvqjY2FiPehs2bFDTpk31/PPPu8oGDhyoiIgI/fjjj3rqqafcDrwbN250rcsHHnggVWJ1ngRu27bN6zPswcHBGjt2rMxM7dq187pdx8XF6dtvv9WaNWtSNaZrTXaFh4e7ksL9+vXTuXPnVKZMGVWpUsWjrvPq2hNPPKHNmze7ys1MTz75pDZt2qRMmTK5rthdjfNE7LXXXnN7T9SZM2c0aNAg7dmzx+flSqkKFSqoQ4cO2rNnj9q3b+/1SvCZM2f0wQcfuO3XSXG2PVOmTHHdni5d7ozHxMTo5MmTqRK70/DhwyVdbuuufBnmc889px9//DFV57du3TodOXIk2SexzvXx7rvvut3tdv78ed1zzz3auXNnqsXmfHHr4MGD9eeff6p27dr6448/XMPbtm2rKlWqaO3aterbt6/X9zccP35cb775pltn8mptwdU4PxLh7eLLwYMHFRMTowsXLrje9XGtnOv8tddec3uM9cCBA+rdu7fPSTR/7C9XM2zYMAUFBenzzz/3ONH45ptvNHnyZEm6oXeyORwONWjQQGam1157TSEhIapTp45reMOGDeVwOFwnbim96yk57f7V6gwaNEj58+fXJ598ooceesjrnacHDx5M9om9vzi33SVLlujXX391GzZlyhR9/PHHqTo/X9sEX1zPtlC6/DhXYGCgZs2a5XGxb+bMmfr8889TdX7S5X7BggULVLVqVW3btk05c+b02KZ8bUdGjhypjBkz6ssvv9Qjjzzi0RYfPnzYrR92vde3L23Vt99+q/nz53ssi5lp3rx5ktz789dze3U6d+6c3njjDdWrV0/nz59XvXr1PNpbX/s9znbryn39yummtD14/vnnvb4jauvWra67pRKuV1/OxRLGn1i7m9I4cBPz56f04B+HDh2yevXquT7nWbBgQWvbtq1169bNGjRoYBkyZDBJFhER4fb54at9Yjixz91+9tln5nA4TJKVKVPGunbtag0aNLDg4GBr0KCB1ahRw+vnMX39DPw///xjlSpVMkmWIUMGa9OmjXXu3Nly5cplWbJkcX32+crP0ZuZTZo0yYKCgkySFS5c2Fq2bGndu3e3xo0buz5DnPAz6s7P4+bKlctatGhhPXr0sBYtWlhkZKRJstKlSyf6+VpvnL/JlZyf003s06vOZUrO53avNH78eAsODnZ9arxRo0bWvXt3a9OmjRUoUMAV05Wfj587d66FhYWZJCtevLh169bNGjZs6Fp/ffv29ZiXr9uQmVnlypVNkhUrVsx69Ohh/fv394jpgQcecMVbqlQpa9u2rXXt2tXq1atnmTJlMkn2xhtvuI2T2Dp3Smw7nDdvnkmykJAQa9WqlfXr18/69+9vq1atSnRaiVm7dq0rDkk2ceJEr/Xi4+OtV69eJsmCgoKsYcOG1q1bNytWrJhJsnTp0tn8+fOTvQwXLlxwrdfIyEhr2bKlNW/e3LJmzWq5c+e2fv36ef29rvY7Xm17TCyeU6dOWcOGDV3rtUqVKta5c2fr1KmTValSxUJCQkyS/fbbb16ne6UdO3a4fvfcuXNbhw4drE2bNhYZGWk5c+b0efmS2k7vvfdek2QBAQFWr14969atm5UqVcoCAgJs2LBhPn0S3Lld7NmzJ1n1nfEVKlTIrfz48eOutiRz5sx2xx13WIcOHSxbtmyWMWNGV3xXfmo5OZ9gdn4i2tunwp2f0c6ePbv99NNPrvJ9+/ZZ+fLlXZ/SrlGjhnXt2tXat29v5cuXt8DAQJNk586dc5tectqCxDjb5sDAQCtfvrx16NDBunTpYrVq1XK1g9HR0bZ69eoUrYPEln/NmjWu7bZw4cLWuXNna9asmaVLl85KlSpl7dq187qvJKdNT+39xezqx93JkydbQECASbKKFSta9+7drWbNmq5j/GOPPeYxzrUcn7xx7p+J7UeTJ0927TP169f3GF6hQgXX8A8++MDrNBJbDwcPHrT06dObJKtZs6b16dPH+vfvb9OmTXPVSc6x4ZdffnEdXzNlymR16tS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      "text/plain": [
       "<Figure size 1200x1200 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Data for Decahose dataset\n",
    "categories = ['Low-Quality Content', 'High-Quality Content']\n",
    "volume_changes = [-0.9, -16.3]  # % change in volume (rounded to 1 decimal)\n",
    "market_share_changes = [17.5, -2.0]  # % change in market share (rounded to 1 decimal)\n",
    "\n",
    "# Data for Twitter Panel dataset\n",
    "volume_changes_panel = [-23.0, -26.9]  # % change in volume (rounded to 1 decimal)\n",
    "market_share_changes_panel = [6.4, -0.9]  # % change in market share (rounded to 1 decimal)\n",
    "\n",
    "# Colors for the updated plot\n",
    "colors_decahose = ['black', 'green']  # Tones of blue for Decahose\n",
    "colors_panel = ['black', 'green']  # Tones of orange for Twitter Panel\n",
    "\n",
    "# Creating a combined plot for both Twitter Panel and Decahose datasets with updated colors\n",
    "fig, axs = plt.subplots(2, 2, figsize=(12, 12), sharey=True)\n",
    "\n",
    "# Titles and data for each subplot\n",
    "datasets = ['Decahose Dataset', 'Twitter Panel Dataset']\n",
    "volume_changes_all = [volume_changes, volume_changes_panel]\n",
    "market_share_changes_all = [market_share_changes, market_share_changes_panel]\n",
    "\n",
    "# Plotting the data for each dataset with different color tones\n",
    "for i, dataset in enumerate(datasets):\n",
    "    # Volume Change subplot\n",
    "    if dataset == 'Decahose Dataset':\n",
    "        colors = colors_decahose\n",
    "    else:\n",
    "        colors = colors_panel\n",
    "\n",
    "    axs[i, 0].bar(categories, volume_changes_all[i], color=colors)\n",
    "    axs[i, 0].set_title(f'{dataset}: Volume Change (%)')\n",
    "    axs[i, 0].set_ylabel('Percentage Change')\n",
    "    axs[i, 0].set_ylim(-30, 20)\n",
    "    axs[i, 0].grid(axis='y', linestyle='--', alpha=0.7)\n",
    "\n",
    "    # Add bold y=0 line\n",
    "    axs[i, 0].axhline(0, color='black', linewidth=2)  # Bold y=0 line\n",
    "\n",
    "    # Market Share Change subplot\n",
    "    axs[i, 1].bar(categories, market_share_changes_all[i], color=colors)\n",
    "    axs[i, 1].set_title(f'{dataset}: Market Share Change (%)')\n",
    "    axs[i, 1].grid(axis='y', linestyle='--', alpha=0.7)\n",
    "\n",
    "    # Add bold y=0 line\n",
    "    axs[i, 1].axhline(0, color='black', linewidth=2)  # Bold y=0 line\n",
    "\n",
    "# Adding a main title\n",
    "fig.suptitle('Changes in Content Volume and Market Share for Twitter Panel and Decahose Datasets', fontsize=16)\n",
    "\n",
    "# Display the combined plots\n",
    "plt.tight_layout(rect=[0, 0.03, 1, 0.95])\n",
    "#plt.savefig('/home/ozturan/covid-conspiracy-narratives/src/musk/submission/figures/newsguard_full_marketshare_change.png', dpi=1200, bbox_inches='tight')\n",
    "plt.show()\n"
   ]
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